Machine Learning

Kunze, S. ; Cecil, A. ; Prehn, C. ; Möller, G. ; Ohlmann, A. ; Wildner, G. ; Thurau, S. ; Unger, K. ; Rößler, U. ; Hölter, S.M. ; Tapio, S. ; Wagner, F. ; Beyerlein, A. ; Theis, F.J. ; Zitzelsberger, H. ; Kulka, U. ; Adamski, J. ; Graw, J. ; Dalke, C.

Posterior subcapsular cataracts are a late effect after acute exposure to 0.5 Gy ionizing radiation in mice.

Int. J. Radiat. Biol., DOI: 10.1080/09553002.2021.1876951 (2021)

Böttcher, A. ; Büttner, M. ; Tritschler, S. ; Sterr, M. ; Aliluev, A. ; Oppenländer, L. ; Burtscher, I. ; Sass, S. ; Irmler, M. ; Beckers, J. ; Ziegenhain, C. ; Enard, W. ; Schamberger, A.C. ; Verhamme, F.M. ; Eickelberg, O. ; Theis, F.J. ; Lickert, H.

Non-canonical Wnt/PCP signalling regulates intestinal stem cell lineage priming towards enteroendocrine and Paneth cell fates.

Nat. Cell Biol. 23, 23-31 (2021)

Karlina, R. ; Lutter, D. ; Miok, V. ; Fischer, D.S. ; Altun, I. ; Schöttl, T. ; Schorpp, K.K. ; Israel, A. ; Cero, C. ; Johnson, J.W. ; Kapser-Fischer, I. ; Böttcher, A. ; Keipert, S. ; Feuchtinger, A. ; Graf, E. ; Strom, T.M. ; Walch, A.K. ; Lickert, H. ; Walzthoeni, T. ; Heinig, M. ; Theis, F.J. ; García-Cáceres, C. ; Cypess, A.M. ; Ussar, S.

Identification and characterization of distinct brown adipocyte subtypes in C57BL/6J mice.

Life Sci. All. 4:e202000924 (2021)

Krautenbacher, N. ; Kabesch, M. ; Horak, E. ; Braun-Fahrländer, C. ; Genuneit, J. ; Boznanski, A. ; von Mutius, E. ; Theis, F.J. ; Fuchs, C. ; Ege, M.J. ; GABRIELA, PASTURE study groups

Asthma in farm children is more determined by genetic polymorphisms and in non-farm children by environmental factors.

Pediatr. Allergy Immunol. 32, 295-304 (2021)

Chlis, N.-K. ; Rausch, L. ; Brocker, T. ; Kranich, J. ; Theis, F.J.

Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning.

Nucleic Acids Res. 48, 11335-11346 (2020)

Lotfollahi, M. ; Naghipourfar, M. ; Theis, F.J. ; Wolf, F.A.

Conditional out-of-distribution generation for unpaired data using transfer VAE.

Bioinformatics 36, 2, i610-i617 (2020)

Kranich, J. ; Chlis, N.-K. ; Rausch, L. ; Latha, A. ; Schifferer, M. ; Kurz, T. ; Foltyn-Arfa Kia, A. ; Simons, M. ; Theis, F.J. ; Brocker, T.

In vivo identification of apoptotic and extracellular vesicle-bound live cells using image-based deep learning.

J. Extra. Vesicles 9:1792683 (2020)

Chlis, N.-K. ; Karlas, A. ; Fasoula, N.-A. ; Kallmayer, M. ; Eckstein, H.H. ; Theis, F.J. ; Ntziachristos, V. ; Marr, C.

A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography.

Photoacoustics 20:100203 (2020)

Ansari, M. ; Fischer, D.S. ; Theis, F.J.

Learning Tn5 sequence bias from ATAC-seq on naked chromatin.

Lect. Notes Comput. Sc. 12396 LNCS, 105-114 (2020)

Holmberg, O. ; Köhler, N. ; Martins, T. ; Siedlecki, J. ; Herold, T. ; Keidel, L. ; Asani, B. ; Schiefelbein, J. ; Priglinger, S. ; Kortuem, K.U. ; Theis, F.J.

Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy.

Nat. Mach. Intell. 2, 719-726 (2020)

Conlon, T.M. ; John-Schuster, G. ; Heide, D. ; Pfister, D. ; Lehmann, M. ; Hu, Y. ; Ertüz, Z. ; López, M.A. ; Ansari, M. ; Strunz, M. ; Mayr, C. ; Ciminieri, C. ; Costa, R. ; Kohlhepp, M.S. ; Guillot, A. ; Güneş, G. ; Jeridi, A. ; Funk, M.C. ; Beroshvili, G. ; Prokosch, S. ; Hetzer, J. ; Verleden, S.E. ; Alsafadi, H.N. ; Lindner, M. ; Burgstaller, G. ; Becker, L. ; Irmler, M. ; Dudek, M. ; Janzen, J. ; Goffin, E. ; Gosens, R. ; Knolle, P. ; Pirotte, B. ; Stöger, T. ; Beckers, J. ; Wagner, D.E. ; Singh, I. ; Theis, F.J. ; Hrabě de Angelis, M. ; O’Connor, T. ; Tacke, F. ; Boutros, M. ; Dejardin, E. ; Eickelberg, O. ; Schiller, H. B. ; Königshoff, M. ; Heikenwalder, M. ; Yildirim, A.Ö.

Inhibition of LTβR signalling activates WNT-induced regeneration in lung.

Nature 588, 151–156 (2020)

Rajewsky, N. ; Almouzni, G. ; Gorski, S.A. ; Aerts, S. ; Amit, I. ; Bertero, M.G. ; Bock, C. ; Bredenoord, A.L. ; Cavalli, G. ; Chiocca, S. ; Clevers, H. ; de Strooper, B. ; Eggert, A. ; Ellenberg, J. ; Fernández, X.M. ; Figlerowicz, M. ; Gasser, S.M. ; Hubner, N. ; Kjems, J. ; Knoblich, J.A. ; Krabbe, G. ; Lichter, P. ; Linnarsson, S. ; Marine, J.C. ; Marioni, J. ; Marti-Renom, M.A. ; Netea, M.G. ; Nickel, D. ; Nollmann, M. ; Novak, H.R. ; Parkinson, H. ; Piccolo, S. ; Pinheiro, I. ; Pombo, A. ; Popp, C. ; Reik, W. ; Roman-Roman, S. ; Rosenstiel, P. ; Schultze, J.L. ; Stegle, O. ; Tanay, A. ; Testa, G. ; Thanos, D. ; Theis, F.J. ; Torres-Padilla, M.E. ; Valencia, A. ; Vallot, C. ; van Oudenaarden, A. ; Vidal, M. ; Voet, T. ; LifeTime Community (Schiller, H. B.) ; LifeTime Community (Ziegler, A.-G.)

LifeTime and improving European healthcare through cell-based interceptive medicine.

Nature 587, 377–386 (2020)

Fischer, D.S. ; Wu, Y. ; Schubert, B. ; Theis, F.J.

Predicting antigen specificity of single T cells based on TCR CDR3 regions.

Mol. Syst. Biol. 16:e9416 (2020)

Strunz, M. ; Simon, L. ; Ansari, M. ; Kathiriya, J.J. ; Angelidis, I. ; Mayr, C. ; Tsidiridis, G. ; Lange, M. ; Mattner, L. ; Yee, M. ; Ogar, P. ; Sengupta, A. ; Kukhtevich, I. ; Schneider, R. ; Zhao, Z. ; Voss, C. ; Stöger, T. ; Neumann, J.H.L. ; Hilgendorff, A. ; Behr, J. ; O'Reilly, M. ; Lehmann, M. ; Burgstaller, G. ; Königshoff, M. ; Chapman, H.A. ; Theis, F.J. ; Schiller, H. B.

Alveolar regeneration through a Krt8+transitional stem cell state that persists in human lung fibrosis.

Nat. Commun. 11:3559 (2020)

Bergen, V. ; Lange, M. ; Peidli, S. ; Wolf, F.A. ; Theis, F.J.

Generalizing RNA velocity to transient cell states through dynamical modeling.

Nat. Biotechnol. 38, 1408–1414 (2020)

Radon, K. ; Saathoff, E. ; Pritsch, M. ; Guggenbühl Noller, J.M. ; Kroidl, I. ; Olbrich, L. ; Thiel, V. ; Diefenbach, M. ; Riess, F. ; Förster, F. ; Theis, F.J. ; Wieser, A. ; Hoelscher, M. ; the KoCo19 collaboration group (Hasenauer, J. ; Castelletti, N. ; Zeggini, E. ; Laxy, M. ; Leidl, R. ; Schwettmann, L.) ; the KoCo19 collaboration group (Fuchs, C.)

Protocol of a population-based prospective COVID-19 cohort study Munich, Germany (KoCo19).

BMC Public Health 20:1036 (2020)

Müller, J.B. ; Geyer, P.E. ; Colaço, A.R. ; Treit, P.V. ; Strauss, M.T. ; Oroshi, M. ; Doll, S. ; Virreira Winter, S. ; Bader, J.M. ; Koehler, N. ; Theis, F.J. ; Santos, A. ; Mann, M.

The proteome landscape of the kingdoms of life.

Nature 582, 592–596 (2020)

Fischer, A. ; Koopmans, T. ; Ramesh, P. ; Christ, S. ; Strunz, M. ; Wannemacher, J. ; Aichler, M. ; Feuchtinger, A. ; Walch, A.K. ; Ansari, M. ; Theis, F.J. ; Schorpp, K.K. ; Hadian, K. ; Neumann, P.A. ; Schiller, H. B. ; Rinkevich, Y.

Post-surgical adhesions are triggered by calcium-dependent membrane bridges between mesothelial surfaces.

Nat. Commun. 11:3068 (2020)

Ziegler, C.G.K. ; Allon, S.J. ; Nyquist, S.K. ; Mbano, I.M. ; Miao, V.N. ; Tzouanas, C.N. ; Cao, Y. ; Yousif, A.S. ; Bals, J. ; Hauser, B.M. ; Feldman, J. ; Muus, C. ; Wadsworth, M.H. ; Kazer, S.W. ; Hughes, T.K. ; Doran, B. ; Gatter, G.J. ; Vukovic, M. ; Taliaferro, F. ; Mead, B.E. ; Guo, Z. ; Wang, J.P. ; Gras, D. ; Plaisant, M. ; Ansari, M. ; Angelidis, I. ; Adler, H. ; Sucre, J.M.S. ; Taylor, C.J. ; Lin, B. ; Waghray, A. ; Mitsialis, V. ; Dwyer, D.F. ; Buchheit, K.M. ; Boyce, J.A. ; Barrett, N.A. ; Laidlaw, T.M. ; Carroll, S.L. ; Colonna, L. ; Tkachev, V. ; Peterson, C.W. ; Yu, A. ; Zheng, H.B. ; Gideon, H.P. ; Winchell, C.G. ; Lin, P.L. ; Bingle, C.D. ; Snapper, S.B. ; Kropski, J.A. ; Theis, F.J. ; Schiller, H. B. ; Zaragosi, L.E. ; Barbry, P. ; Leslie, A. ; Kiem, H.P. ; Flynn, J.L. ; Fortune, S.M. ; Berger, B. ; Finberg, R.W. ; Kean, L.S. ; Garber, M. ; Schmidt, A.G. ; Lingwood, D. ; Shalek, A.K. ; Ordovas-Montanes, J.

SARS-CoV-2 receptor ACE2 is an interferon-stimulated gene in human airway epithelial cells and is detected in specific cell subsets across tissues.

Cell 181, 1016-1035 (2020)

Sachs, S. ; Bastidas-Ponce, A. ; Tritschler, S. ; Bakhti, M. ; Böttcher, A. ; Sánchez-Garrido, M.A. ; Tarquis Medina, M. ; Kleinert, M. ; Fischer, K. ; Jall, S. ; Harger, A. ; Bader, E. ; Roscioni, S. ; Ussar, S. ; Feuchtinger, A. ; Yesildag, B. ; Neelakandhan, A. ; Jensen, C.B. ; Cornu, M. ; Yang, B. ; Finan, B. ; DiMarchi, R.D. ; Tschöp, M.H. ; Theis, F.J. ; Hofmann, S.M. ; Müller, T.D. ; Lickert, H.

Author Correction: Targeted pharmacological therapy restores β-cell function for diabetes remission (Nature Metabolism, (2020), 2, 2, (192-209), 10.1038/s42255-020-0171-3).

Nat. Metab. 2, 380 (2020)

Kozak, E.L. ; Palit, S. ; Miranda Rodriguez, J.R. ; Janjic, A. ; Böttcher, A. ; Lickert, H. ; Enard, W. ; Theis, F.J. ; López-Schier, H.

Epithelial planar bipolarity emerges from Notch-mediated asymmetric inhibition of Emx2.

Curr. Biol. 30, 1142-1151 (2020)

Lähnemann, D. ; Köster, J. ; Szczurek, E. ; McCarthy, D.J. ; Hicks, S.C. ; Robinson, M.D. ; Vallejos, C.A. ; Campbell, K.R. ; Beerenwinkel, N. ; Mahfouz, A. ; Pinello, L. ; Skums, P. ; Stamatakis, A. ; Attolini, C.S.O. ; Aparicio, S. ; Baaijens, J. ; Balvert, M. ; Barbanson, B.d. ; Cappuccio, A. ; Corleone, G. ; Dutilh, B.E. ; Florescu, M. ; Guryev, V. ; Holmer, R. ; Jahn, K. ; Lobo, T.J. ; Keizer, E.M. ; Khatri, I. ; Kielbasa, S.M. ; Korbel, J.O. ; Kozlov, A.M. ; Kuo, T.H. ; Lelieveldt, B.P.F. ; Mandoiu, I.I. ; Marioni, J.C. ; Marschall, T. ; Mölder, F. ; Niknejad, A. ; Raczkowski, L. ; Reinders, M. ; Ridder, J.d. ; Saliba, A.E. ; Somarakis, A. ; Stegle, O. ; Theis, F.J. ; Yang, H. ; Zelikovsky, A. ; McHardy, A.C. ; Raphael, B.J. ; Shah, S.P. ; Schönhuth, A.

Eleven grand challenges in single-cell data science.

Genome Biol. 21:31 (2020)

Strunz, M. ; Simon, L. ; Ansari, M. ; Mattner, L. ; Angelidis, I. ; Mayr, C. ; Kathiriya, J. ; Yee, M. ; Ogar, P. ; Voss, C. ; Stöger, T. ; Kukhtevich, I. ; Schneider, R. ; Lehmann, M. ; Koenigshoff, M. ; Burgstaller, G. ; O'Reilly, M. ; Chapman, H. ; Theis, F.J. ; Schiller, H. B.

Fate trajectory modeling reveals convergence of airway derived progenitors and AT2 cells on transient KRT8+alveolar cell state during lung regeneration.

Wound Repair Regen. 28, A7-A7 (2020)

van der Wijst, M. ; de Vries, D.H. ; Groot, H.E. ; Trynka, G. ; Hon, C.C. ; Bonder, M.J. ; Stegle, O. ; Nawijn, M.C. ; Idaghdour, Y. ; van der Harst, P. ; Ye, C.J. ; Powell, J. ; Theis, F.J. ; Mahfouz, A. ; Heinig, M. ; Franke, L.

The single-cell eQTLGen consortium.

eLife 9:e52155 (2020)

Angerer, P. ; Fischer, D.S. ; Theis, F.J. ; Scialdone, A. ; Marr, C.

Automatic identification of relevant genes from low-dimensional embeddings of single-cell RNA-seq data.

Bioinformatics 36, 4291-4295 (2020)

Raimundez-Alvarez, E. ; Keller, S. ; Ebert, K. ; Hug, S. ; Theis, F.J. ; Maier, D. ; Luber, B. ; Hasenauer, J.

Model-based analysis of response and resistance factors of cetuximab treatment in gastric cancer cell lines.

PLoS Comput. Biol. 16:e1007147 (2020)

Arloth, J. ; Eraslan, G. ; Andlauer, T.F.M. ; Martins, J. ; Iurato, S. ; Kühnel, B. ; Waldenberger, M. ; Frank, J. ; Gold, R. ; Hemmer, B. ; Luessi, F. ; Nischwitz, S. ; Paul, F. ; Wiendl, H. ; Gieger, C. ; Heilmann-Heimbach, S. ; Kacprowski, T. ; Laudes, M. ; Meitinger, T. ; Peters, A. ; Rawal, R. ; Strauch, K. ; Lucae, S. ; Müller-Myhsok, B. ; Rietschel, M. ; Theis, F.J. ; Binder, E.B. ; Müller, N.S.

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

PLoS Comput. Biol. 16:e1007616 (2020)

Sachs, S. ; Bastidas-Ponce, A. ; Tritschler, S. ; Bakhti, M. ; Böttcher, A. ; Sánchez-Garrido, M.A. ; Tarquis Medina, M. ; Kleinert, M. ; Fischer, K. ; Jall, S. ; Harger, A. ; Bader, E. ; Roscioni, S. ; Ussar, S. ; Feuchtinger, A. ; Yesildag, B. ; Neelakandhan, A. ; Jensen, C.B. ; Cornu, M. ; Yang, B. ; Finan, B. ; DiMarchi, R.D. ; Tschöp, M.H. ; Theis, F.J. ; Hofmann, S.M. ; Müller, T.D. ; Lickert, H.

Targeted pharmacological therapy restores β-cell function for diabetes remission.

Nat. Metab. 2, 192-209 (2020)

Lauffer, F. ; Jargosch, M. ; Baghin, V. ; Krause, L. ; Kempf, W. ; Absmaier-Kijak, M. ; Morelli, M. ; Madonna, S. ; Marsais, F. ; Lepescheux, L. ; Albanesi, C. ; Müller, N.S. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Biedermann, T. ; Vandeghinste, N. ; Steidl, S. ; Eyerich, K.

IL-17C amplifies epithelial inflammation in human psoriasis and atopic eczema.

J. Eur. Acad. Dermatol. Venereol. 34, 800-809 (2020)

Förster, K. ; Ertl-Wagner, B. ; Ehrhardt, H. ; Busen, H. ; Sass, S. ; Pomschar, A. ; Naehrlich, L. ; Schulze, A. ; Flemmer, A.W. ; Hübener, C. ; Eickelberg, O. ; Theis, F.J. ; Dietrich, O. ; Hilgendorff, A.

Altered relaxation times in MRI indicate bronchopulmonary dysplasia.

Thorax 75, 184-187 (2020)

Pitea, A. ; Kondofersky, I. ; Sass, S. ; Theis, F.J. ; Müller, N.S. ; Unger, K.

Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches?

Brief. Bioinform. 21, 272-281 (2020)

Cruceanu, C. ; Dony, L. ; Kontira, A.C. ; Fischer, D.S. ; Roeh, S. ; DiGiaimo, R. ; Cappello, S. ; Theis, F.J. ; Binder, E.B.

Brain organoids as models of the developing human brain: deciphering the molecular signature of prenatal stress.

Eur. Neuropsychopharmacol. 29, S7-S8 (2019)

Thomas, J. ; Küpper, M. ; Batra, R. ; Jargosch, M. ; Atenhan, A. ; Baghin, V. ; Krause, L. ; Lauffer, F. ; Biedermann, T. ; Theis, F.J. ; Eyerich, K. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Garzorz-Stark, N.

Is the humoral immunity dispensable for the pathogenesis of psoriasis? (vol 33, pg 115, 2019).

J. Eur. Acad. Dermatol. Venereol. 33, 2380-2380 (2019)

Theis, F.J. ; Ludwig, T.

Munich School for Data Science (MUDS) – Eine Graduiertenschule für Data Science in München.

Inf.-Spektrum, DOI: 10.1007/s00287-019-01220-y (2019)

Holmberg, O. ; Kortuem, K.U. ; Koehler, N. ; Theis, F.J.

Predicting retinal thickness from fundus images across modalities using deep learning.

Invest. Ophthalmol. Vis. Sci. 60 (2019)

Böttcher, A. ; Tritschler, S. ; Yang, K. ; Theis, F.J. ; Lickert, H. ; Wolf, E. ; Kemter, E.

Studying in vivo beta cell maturation in pigs by scRNAseq.

Xenotransplantation 26 (2019)

Arloth, J. ; Eraslan, G. ; Andlauer, T. ; Gieger, C. ; Gold, R. ; Heilmann-Heimbach, S. ; Kacprowski, T. ; Meitinger, T. ; Laudes, M. ; Luessi, F. ; Müller-Myhsok, B. ; Nischwitz, S. ; Peters, A. ; Paul, F. ; Rawal, R. ; Strauch, K. ; Wiendl, H. ; Hemmer, B. ; Theis, F.J. ; Binder, E. ; Müller, N.S.

Identification of functionally relevant genetic variants associated with multiple sclerosis using deep learning.

Mult. Scler. J. 25, 906-907 (2019)

Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.

Preface.

Lect. Notes Comput. Sc. 11731 LNCS, v-vii (2019)

Rausch, L. ; Kranich, J. ; Chlis, N.-K. ; Schifferer, M. ; Simons, M. ; Theis, F.J. ; Brocker, T.

Analysis of EV-decorated CD8+T cells during viral infection.

Eur. J. Immunol. 49, 88-88 (2019)

Musumeci, A. ; Lutz, K. ; Dursun, E. ; Sie, C. ; Ziegenhain, C. ; Bagnoli, J. ; Luecken, M. ; Korn, T. ; Enard, W. ; Theis, F.J. ; Krug, A.

Identification of a DC precursor population with pDC and cDC potential responding to endosomal TLR stimulation with increased pDC output.

Eur. J. Immunol. 49, 48-48 (2019)

Bakhti, M. ; Scheibner, K. ; Tritschler, S. ; Bastidas-Ponce, A. ; Tarquis-Medina, M. ; Theis, F.J. ; Lickert, H.

Establishment of a high-resolution 3D modeling system for studying pancreatic epithelial cell biology in vitro.

Mol. Metab. 30, 16-29 (2019)

Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.

Preface.

Lect. Notes Comput. Sc. 11727 LNCS, v-vii (2019)

Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.

Preface.

Lect. Notes Comput. Sc. 11728 LNCS, v-vii (2019)

Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.

Preface.

Lect. Notes Comput. Sc. 11729 LNCS, v-vii (2019)

Mameishvili, E. ; Serafimidis, I. ; Iwaszkiewicz, S. ; Lesche, M. ; Reinhardt, S. ; Bölicke, N. ; Büttner, M. ; Stellas, D. ; Papadimitropoulou, A. ; Szabolcs, M. ; Anastassiadis, K. ; Dahl, A. ; Theis, F.J. ; Efstratiadis, A. ; Gavalas, A.

Aldh1b1 expression defines progenitor cells in the adult pancreas and is required for Kras-induced pancreatic cancer.

Proc. Natl. Acad. Sci. U.S.A. 116, 20679-20688 (2019)

Ashuach, T. ; Fischer, D.S. ; Kreimer, A. ; Ahituv, N. ; Theis, F.J. ; Yosef, N.

MPRAnalyze: Statistical framework for massively parallel reporter assays.

Genome Biol. 20:183 (2019)

Czamara, D. ; Eraslan, G. ; Lahti, J. ; Figueiredo, A.S. ; Girchenko, P. ; Lahti-Pulkkinen, M. ; Hämäläinen, E. ; Kajantie, E. ; Laivuori, H. ; Villa, P. ; Reynolds, R. ; Müller, N.S. ; Theis, F.J. ; Räikkönen, K. ; Binder, E.

Genotype, prenatal environment or both-what shapes the newborn´s epigenome?

Eur. Neuropsychopharmacol. 29, 1037-1037 (2019)

Schaupp, S. ; Budde, M. ; Kondofersky, I. ; Papiol, S. ; Heilbronner, U. ; Gade, K. ; Anderson-Schmidt, H. ; Kalman, J. ; Senner, F. ; Andlauer, T.F.M. ; Rietschel, M. ; Degenhardt, F. ; Müller, N.S. ; Theis, F.J. ; Schulze, T.

Polygenic risk score analysis of trajectories of cognitive performance in psychiatric patients.

Eur. Neuropsychopharmacol. 29, 1161-1161 (2019)

Schulte, E. ; Kondofersky, I. ; Budde, M. ; Adorjan, K. ; Aldinger, F. ; Anderson-Schmidt, H. ; Gade, K. ; Heilbronner, U. ; Kalman, J. ; Papiol, S. ; Theis, F.J. ; Falkai, P. ; Müller, N.S. ; Schulze, T.G.

Polygenic burden analysis of longitudinal clusters of psychopathological features in a cross-diagnostic group of individuals with severe mental illness.

Eur. Neuropsychopharmacol. 29, 1257-1258 (2019)

Weberpals, J. ; Becker, T. ; Schmich, F. ; Ruettinger, D. ; Theis, F.J. ; Bauer-Mehren, A.

Deep learning-based propensity score computation: Cohort study in second line treated advanced non-small cell lung cancer (aNSCLC) patients.

Pharmacoepidemiol. Drug Saf. 28, 585-586 (2019)

Tirier, S.M. ; Park, J. ; Preußer, F. ; Amrhein, L. ; Gu, Z. ; Steiger, S. ; Mallm, J.P. ; Krieger, T. ; Waschow, M. ; Eismann, B. ; Gut, M. ; Gut, I.G. ; Rippe, K. ; Schlesner, M. ; Theis, F.J. ; Fuchs, C. ; Ball, C.R. ; Glimm, H. ; Conrad, C.

Pheno-seq - linking visual features and gene expression in 3D cell culture systems.

Sci. Rep. 9:12367 (2019)

Lotfollahi, M. ; Wolf, F.A. ; Theis, F.J.

scGen predicts single-cell perturbation responses.

Nat. Methods 16, 715-721 (2019)

Uzbas, F. ; Opperer, F. ; Sönmezer, C. ; Shaposhnikov, D. ; Sass, S. ; Krendl, C. ; Angerer, P. ; Theis, F.J. ; Müller, N.S. ; Drukker, M.

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis.

Genome Biol. 20:155 (2019)

Caicedo, J.C. ; Roth, J. ; Goodman, A. ; Becker, T. ; Karhohs, K.W. ; Broisin, M. ; Molnar, C. ; McQuin, C. ; Singh, S. ; Theis, F.J. ; Carpenter, A.E.

Evaluation of deep learning strategies for nucleus segmentation in fluorescence images.

Cytometry A 95, 952-965 (2019)

Patil, S. ; Heuser, C. ; de Almeida, G.P. ; Theis, F.J. ; Zielinski, C.E.

Meeting the challenges of high-dimensional single-cell data analysis in immunology.

Front. Immunol. 10:1515 (2019)

Erhard, F. ; Baptista, M.A.P. ; Krammer, T. ; Hennig, T. ; Lange, M. ; Arampatzi, P. ; Jürges, C.S. ; Theis, F.J. ; Saliba, A.-E. ; Dölken, L.

scSLAM-seq reveals core features of transcription dynamics in single cells.

Nature 571, 419-423 (2019)

Hawe, J. ; Theis, F.J. ; Heinig, M.

Inferring interaction networks from multi-omics data.

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Current best practices in single-cell RNA-seq analysis: A tutorial.

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A cellular census of human lungs identifies novel cell states in health and in asthma.

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Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns.

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Comprehensive single cell mRNA profiling reveals a detailed roadmap for pancreatic endocrinogenesis.

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A map of beta-cell differentiation.

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Dynamic modelling of an ACADS genotype in fatty acid oxidation - Application of cellular models for the analysis of common genetic variants.

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Schiller, H. B. ; Montoro, D.T. ; Simon, L. ; Rawlins, E.L. ; Meyer, K.B. ; Strunz, M. ; Vieira Braga, F. ; Timens, W. ; Koppelman, G.H. ; Budinger, G.R.S. ; Burgess, J.K. ; van den Berge, M. ; Theis, F.J. ; Regev, A. ; Kaminski, N. ; Rajagopal, J. ; Teichmann, S.A. ; Misharin, A.V. ; Nawijn, M.C.

The Human Lung Cell Atlas: A high-resolution reference map of the human lung in health and disease.

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Common patterns of gene regulation associated with Cesarean section and the development of islet autoimmunity - indications of immune cell activation.

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Deep learning: New computational modelling techniques for genomics.

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Inferring population dynamics from single-cell RNA-sequencing time series data.

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A strategy for high-dimensional multivariable analysis classifies childhood asthma phenotypes from genetic, immunological, and environmental factors.

Allergy 74, 1364-1373 (2019)

Wang, R. ; Thomas, J. ; Batra, R. ; Biedermann, T. ; Theis, F.J. ; Eyerich, S. ; Eyerich, K.

CD23 is a biomarker of clinical response to IgE-specific immunoadsorption in patients with severe atopic eczema.

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PAGA: Graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells.

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An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics.

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IRE1α-XBP1s pathway promotes prostate cancer by activating c-MYC signaling.

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Single-cell RNA-seq denoising using a deep count autoencoder.

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Kaderali, L. ; Theis, F.J. ; Ganusov, V.V. ; Ciupe, S.M. ; Mehr, R. ; Ribeiro, R.M. ; Hernandez-Vargas, E.A.

Editorial: Integrative computational systems biology approaches in immunology and medicine.

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A test metric for assessing single-cell RNA-seq batch correction.

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Metabolic regulation of pluripotency and germ cell fate through alpha-ketoglutarate.

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Is the humoral immunity dispensable for the pathogenesis of psoriasis?

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MicroRNA as an integral part of cell communication: Regularized target prediction and network prediction.

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Information theoretic concepts to unravel cell–cell communication.

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Data driven computational modeling of hematopoiesis in myelodysplastic syndromes unveils differences in hematopoietic stem cell kinetics compared to age-matched healthy controls.

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Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data.

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Increasing neural stem cell division asymmetry and quiescence are predicted to contribute to the age-related decline in neurogenesis.

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Efficient parameter estimation enables the prediction of drug response using a mechanistic pan-cancer pathway model.

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Quantitative MRI measurements to detect pulmonary hypertension in bronchopulomnary dysplasia.

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Diagnosis of bronchopulmonary dysplasia using magnetic resonance imaging analysis.

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The human lung cell atlas: A comprehensive reference map for all cell types in the healthy human lung.

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Impulse model-based differential expression analysis of time course sequencing data.

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Impact of brain fatty acid signaling on peripheral insulin action in mice.

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Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies.

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LNA++: Linear noise approximation with first and second order sensitivities.

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The role of humoral immunity in the pathogenesis of psoriasis.

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Mit Big Data zur personalisierten Diabetesprävention.

Diabetologe 14, 486-492 (2018)

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Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering.

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Statistical single cell multi-omics integration.

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Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm.

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MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data.

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Inductive and selective effects of GSK3 and MEK inhibition on nanog heterogeneity in embryonic stem cells.

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Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics.

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Type I immune response induces keratinocyte necroptosis and is associated with interface dermatitis.

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SCANPY: Large-scale single-cell gene expression data analysis.

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Maternal whole blood cell miRNA-340 is elevated in gestational diabetes and inversely regulated by glucose and insulin.

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Lifetime study in mice after acute low-dose ionizing radiation: A multifactorial study with special focus on cataract risk.

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Early identification of bronchopulmonary dysplasia using novel biomarkers by proteomic screening.

Am. J. Respir. Crit. Care Med. 197, 1076-1080 (2018)

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Toll-like receptor 7/8 agonists stimulate plasmacytoid dendritic cells to initiate T(H)17-deviated acute contact dermatitis in human subjects.

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Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young.

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The Human Cell Atlas.

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Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway.

Nat. Commun. 8:1483 (2017)

Dirmeier, S. ; Fuchs, C. ; Müller, N.S. ; Theis, F.J.

netReg: Network-regularized linear models for biological association studies.

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Model based targeting of IL-6-induced inflammatory responses in cultured primary hepatocytes to improve application of the JAK inhibitor ruxolitinib.

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GATA2/3-TFAP2A/C transcription factor network couples human pluripotent stem cell differentiation to trophectoderm with repression of pluripotency.

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Single cells make big data: New challenges and opportunities in transcriptomics.

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pulver: An R package for parallel ultra-rapid p-value computation for linear regression interaction terms.

BMC Bioinformatics 18:429 (2017)

Garzorz-Stark, N. ; Lauffer, F. ; Krause, L. ; Gross, O. ; Traidl-Hoffmann, C. ; Theis, F.J. ; Schmidt-Weber, C. ; Biedermann, T. ; Eyerich, S. ; Eyerich, K.

TLR7/8 agonists stimulate plasmacytoid dendritic cells to initiate a Th17-deviated acute contact dermatitis in humans.

J. Invest. Dermatol. 137, S275-S275 (2017)

Lauffer, F. ; Jargosch, M. ; Krause, L. ; Garzorz-Stark, N. ; Franz, R. ; Roenneberg, S. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C. ; Eyerich, S. ; Eyerich, K.

Interface Dermatitis is characterized by a type I immune response and an epidermal reaction to IFN-gamma and TNF-alpha.

J. Invest. Dermatol. 137, S254-S254 (2017)

Eulenberg, P. ; Köhler, N. ; Blasi, T. ; Filby, A. ; Carpenter, A.E. ; Rees, P. ; Theis, F.J. ; Wolf, F.A.

Reconstructing cell cycle and disease progression using deep learning.

Nat. Commun. 8:463 (2017)

Krautenbacher, N. ; Theis, F.J. ; Fuchs, C.

Correcting classifiers for sample selection bias in two-phase case-control studies.

Comput. Math. Methods Med. 2017:7847531 (2017)

Tritschler, S. ; Theis, F.J. ; Lickert, H. ; Böttcher, A.

Systematic single-cell analysis provides new insights into heterogeneity and plasticity of the pancreas.

Mol. Metab. 6, 974-990 (2017)

Budde, M. ; Kondofersky, I. ; Adorjan, K. ; Aldinger, F. ; Anderson-Schmidt, H. ; Andlauer, T.F. ; Flatau, L. ; Gade, K. ; Heilbronner, U. ; Kalman, J. ; Papiol, S. ; Theis, F.J. ; Falkai, P. ; Müller, N.S. ; Schulze, T.G.

Integrating polygenic allele burden information and phenomic data to characterize complex disease trajectories in severe mental illness.

Eur. Neuropsychopharmacol. 27, 3, S406 (2017)

Heilbronner, U. ; Jain, G. ; Kaurani, L. ; Kondofersky, I. ; Budde, M. ; Gade, K. ; Kalman, J. ; Adorjan, K. ; Aldinger, F. ; Anderson-Schmidt, H. ; Müller, N.S. ; Theis, F.J. ; Falkai, P. ; Fischer, A. ; Schulze, T.G.

The Role of micrornas in the course of servere mental disorders.

Eur. Neuropsychopharmacol. 27, 3, S456-S457 (2017)

Comes, A. ; Aldinger, F. ; Kondofersky, I. ; Adorjan, K. ; Anderson-Schmidt, H. ; Andlauer, T.F. ; Budde, M. ; Gade, K. ; Heilbronner, U. ; Kalman, J. ; Papiol, S. ; Theis, F.J. ; Falkai, P. ; Müller, N.S. ; Schulze, T.G.

Polygenic burden analysis of longitudinal clusters of quality of life and functioning in patients with severe mental illness.

Eur. Neuropsychopharmacol. 27, 3, S408-S409 (2017)

Schulte, E. ; Kondofersky, I. ; Budde, M. ; Adorjan, K. ; Aldinger, F. ; Anderson-Schmidt, H. ; Andlauer, T.F. ; Gade, K. ; Heilbronner, U. ; Kalman, J. ; Papiol, S. ; Theis, F.J. ; Falkai, P. ; Müller, N.S. ; Schulze, T.G.

Polygenic burden analysis of longitudinal clusters of psychopathological features in a cross-diagnostic group of individuals with severe mental illness.

Eur. Neuropsychopharmacol. 27, 3, S401-S402 (2017)

Kazeroonian, A. ; Theis, F.J. ; Hasenauer, J.

A scalable moment-closure approximation for large-scale biochemical reaction networks.

Bioinformatics 33, i293-i300 (2017)

Peng, T. ; Thorn, K. ; Schroeder, T. ; Wang, L. ; Theis, F.J. ; Marr, C. ; Navab, N.

A BaSiC tool for background and shading correction of optical microscopy images.

Nat. Commun. 8:14836 (2017)

Milger, K. ; Götschke, J. ; Krause, L. ; Nathan, P. ; Alessandrini, F. ; Tufman, A. ; Fischer, R. ; Bartel, S. ; Theis, F.J. ; Behr, J. ; Dehmel, S. ; Müller, N.S. ; Kneidinger, N. ; Krauss-Etschmann, S.

Identification of a plasma miRNA biomarker-signature for allergic asthma: A translational approach.

Allergy 72, 1962-1971 (2017)

Ballnus, B. ; Hug, S. ; Hatz, K. ; Görlitz, L. ; Hasenauer, J. ; Theis, F.J.

Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.

BMC Syst. Biol. 11:63 (2017)

Conlon, T.M. ; Hackl, M. ; Bartel, J. ; Krumsiek, J. ; Irmler, M. ; Beckers, J. ; Theis, F.J. ; Eickelberg, O. ; Yildirim, A.Ö.

2d cross-omics integrated enrichment analysis of human and mice COPD lungs reveal novel pathological mechanisms of disease progression.

Am. J. Respir. Crit. Care Med. 195 (2017)

Bartel, S. ; Schulz, N. ; Alessandrini, F. ; Schamberger, A.C. ; Pagel, P. ; Theis, F.J. ; Milger, K. ; Nößner, E. ; Stick, S.M. ; Kicic, A. ; Eickelberg, O. ; Freishtat, R.J. ; Krauss-Etschmann, S.

Pulmonary microRNA profiles identify involvement of Creb1 and Sec14l3 in bronchial epithelial changes in allergic asthma.

Sci. Rep. 7:46026 (2017)

Chlis, N.-K. ; Wolf, F.A. ; Theis, F.J.

Model-based branching point detection in single-cell data by K-Branches clustering.

Bioinformatics 33, 3211-3219 (2017)

Hilgendorff, A. ; Foerster, K. ; Sass, S. ; Stoecklein, S. ; Dietrich, O. ; Pomschar, A. ; Schulze, A. ; Huebener, C. ; Theis, F.J. ; Erhardt, H. ; Flemmer, A.W. ; Ertl-Wagner, B.

Discrimination of pulmonary changes in neonatal chronic lung disease by a new Mri score.

Am. J. Respir. Crit. Care Med. 195 (2017)

Piasecka, J. ; Hennig, H. ; Theis, F.J. ; Rees, P. ; Summers, H.D. ; Thornton, C.A.

Label free identification of peripheral blood eosinophils using high-throughput imaging flow cytometry.

J. Allergy Clin. Immunol. 139, AB163-AB163 (2017)

Florea, A.M. ; Varghese, E. ; McCallum, J.E. ; Mahgoub, S. ; Helmy, I. ; Varghese, S. ; Gopinath, N. ; Sass, S. ; Theis, F.J. ; Reifenberger, G. ; Büsselberg, D.

Calcium-regulatory proteins as modulators of chemotherapy in human neuroblastoma.

Oncotarget 8, 22876-22893 (2017)

Kuepper, M.K. ; Thomas, J. ; Krause, L. ; Müller, N.S. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, K. ; Eyerich, S. ; Garzorz-Stark, N.

Characterization of multiple B cell subsets in peripheral blood and skin biopsies of psoriasis patients identifies a correlation of plasma and regulatory B cells and disease severity.

Exp. Dermatol. 26, E69-E70 (2017)

Garzorz-Stark, N. ; Krause, L. ; Lauffer, F. ; Atenhan, A. ; Thomas, J. ; Theis, F.J. ; Müller, N.S. ; Biedermann, T. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

The imiquimod model as a model for psoriasis and/or eczema in humans?

Exp. Dermatol. 26, E68-E68 (2017)

Lauffer, F. ; Krause, L. ; Franz, R. ; Garzorz-Stark, N. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

Interface dermatitis shows a distinctive molecular signature independent from individual disease background.

Exp. Dermatol. 26, E61-E61 (2017)

Blasi, T. ; Buettner, F. ; Strasser, M. ; Marr, C. ; Theis, F.J.

CgCorrect: A method to correct for confounding cell-cell variation due to cell growth in single-cell transcriptomics.

Phys. Biol. 14:036001 (2017)

Hilsenbeck, O. ; Schwarzfischer, M. ; Loeffler, D. ; Dimopoulos, S. ; Hastreiter, S. ; Marr, C. ; Theis, F.J. ; Schroeder, T.

fastER: A user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy.

Bioinformatics 33, 2020-2028 (2017)

Buggenthin, F. ; Buettner, F. ; Hoppe, P.S. ; Endele, M. ; Kroiss, M. ; Strasser, M. ; Schwarzfischer, M. ; Loeffler, D. ; Kokkaliaris, K.D. ; Hilsenbeck, O. ; Schroeder, T. ; Theis, F.J. ; Marr, C.

Prospective identification of hematopoietic lineage choice by deep learning.

Nat. Methods, DOI: 10.1038/nmeth.4182 (2017)

Jagiella, N. ; Rickert, D. ; Theis, F.J. ; Hasenauer, J.

Parallelization and high-performance computing enables automated statistical inference of multi-scale models.

Cell Syst. 4, 194–206.e9 (2017)

Fröhlich, F. ; Theis, F.J. ; Rädler, J.O. ; Hasenauer, J.

Parameter estimation for dynamical systems with discrete events and logical operations.

Bioinformatics 33, 1049-1056 (2017)

Fröhlich, F. ; Kaltenbacher, B. ; Theis, F.J. ; Hasenauer, J.

Scalable parameter estimation for genome-scale biochemical reaction networks.

PLoS Comput. Biol. 13:e1005331 (2017)

von Toerne, C. ; Laimighofer, M. ; Achenbach, P. ; Beyerlein, A. ; de Las Heras Gala, T. ; Krumsiek, J. ; Theis, F.J. ; Ziegler, A.-G. ; Hauck, S.M.

Peptide serum markers in islet autoantibody-positive children.

Diabetologia 60, 287-295 (2017)

Senís, E. ; Mockenhaupt, S. ; Rupp, D. ; Bauer, T. ; Paramasivam, N. ; Knapp, B. ; Gronych, J. ; Grosse, S.D. ; Windisch, M.P. ; Schmidt, F. ; Theis, F.J. ; Eils, R. ; Lichter, P. ; Schlesner, M. ; Bartenschlager, R. ; Grimm, D.

TALEN/CRISPR-mediated engineering of a promoterless anti-viral RNAi hairpin into an endogenous miRNA locus.

Nucleic Acids Res. 45:e3 (2017)

Förster, K. ; Sass, S. ; Dietrich, O. ; Pomschar, A. ; Nährlich, L. ; Schulze, A. ; Flemmer, A.W. ; Ehrhardt, H. ; Hübener, C. ; Eickelberg, O. ; Theis, F.J. ; Ertl-Wagner, B. ; Hilgendorff, A.

LSC Abstract – Early biomarkers indicating the development of neonatal chronic lung disease defined by clinical and imaging parameters.

Eur. Respir. J. 48, PP104 (2016)

Much, D. ; Beyerlein, A. ; Kindt, A. ; Krumsiek, J. ; Rossbauerl, M. ; Hofelich, A. ; Hivner, S. ; Herbst, M. ; Römisch-Margl, W. ; Prehn, C. ; Adamski, J. ; Kastenmüller, G. ; Theis, F.J. ; Ziegler, A.-G. ; Hummel, S.

Lactation is associated with altered metabolomic signatures in women with gestational diabetes.

Diabetologia 59, S187-S187 (2016)

Stoecker, K. ; Sass, S. ; Theis, F.J. ; Hauner, H. ; Pfaffl, M.W.

Inhibition of fat cell differentiation in 3T3-L1 pre-adipocytes by all-trans retinoic acid: Integrative analysis of transcriptomic and phenotypic data.

Biomol. Detect. Quantif. 11, 31-44 (2016)

Huypens, P. ; Sass, S. ; Wu, M. ; Dyckhoff, D. ; Tschöp, M.H. ; Theis, F.J. ; Marschall, S. ; Hrabě de Angelis, M. ; Beckers, J.

Epigenetic germline inheritance of diet-induced obesity and insulin resistance.

Obstet. Gynecol. Surv. 71, 719-720 (2016)

Luber, B. ; Keller, S. ; Zwingenberger, G. ; Ebert, K. ; Maier, D. ; Geier, B. ; Theis, F.J. ; Hasenauer, J. ; Huge, S. ; Meyer-Hermann, M. ; Dehghany, J. ; Walch, A.K. ; Aichler, M. ; Lordick, F. ; Haffner, I.

Identification of predictive response and resistance factors to targeted therapy in gastric cancer using a systems medicine approach.

Eur. J. Cancer 68, S135-S135 (2016)

Fröhlich, F. ; Shadrin, A. ; Kessler, T. ; Wierling, C. ; Heinig, M. ; Theis, F.J. ; Lange, B.M. ; Lehrach, H. ; Hasenauer, J.

Large-scale modeling of cancer signaling: Mechanistic modeling meets Big Data.

Eur. J. Cancer 68, S44-S44 (2016)

Hross, S. ; Fiedler, A. ; Theis, F.J. ; Hasenauer, J.

Quantitative comparison of competing PDE models for Pomlp dynamics in fission yeast.

In: (Foundations of Systems Biology in Engineering - FOSBE 2016, 9—12 October 2016, Magdeburg). 2016. 264-269 (IFAC PapersOnline ; 49-26)

Kong, B. ; Bruns, P. ; Behler, N. ; Schlitter, A.M. ; Friess, H. ; Erkan, M. ; Theis, F.J. ; Esposito, I. ; Michalski, C.W. ; Kleeff, J.

Oncogenic Kras promotes early pancreatic carcinogenesis by perpetuating elements of natural inflammatory response.

Pancreatol. 16, S. 11 (2016)

González-Valllinas, M. ; Albrecht, M. ; Pitea, A. ; Rodriguez-Paredes, M. ; Stichel, D. ; Sass, S. ; Gutekunst, J. ; Schmitt, J. ; Muley, T. ; Meister, M. ; Warth, A. ; Schirmacher, P. ; Theis, F.J. ; Müller, N.S. ; Matthäus, F. ; Breuhahn, K.

Abstract 1945: Identification of a miRNA/mRNA network driving non-small cell lung cancer (NSCLC) dissemination.

Cancer Res. 76 (2016)

Sacher, A. ; Theis, F.J.

Einzigartige Zellen: Computerbasierte Methoden verbessern die Einzelzell-Analyse.

Laborpraxis, DOI: undefined (2016)

Theis, F.J.

Big Data for small cells - neue Software zur Beobachtung einzelner Zellen.

https://www.bsse.ethz.ch/csd/software/ttt-and-qtfy.html (2016)

Feigelman, J. ; Ganscha, S. ; Hastreiter, S. ; Schwarzfischer, M. ; Filipczyk, A. ; Schröder, T. ; Theis, F.J. ; Marr, C. ; Claassen, M.

Analysis of cell lineage trees by exact bayesian inference identifies negative autoregulation of nanog in mouse embryonic stem cells.

Cell Syst. 3, 480-490 (2016)

Bortsova, G. ; Sterr, M. ; Wang, L. ; Milletari, F. ; Navab, N. ; Böttcher, A. ; Lickert, H. ; Theis, F.J. ; Peng, T.

Mitosis detection in intestinal crypt images with hough forest and conditional random fields.

Lect. Notes Comput. Sc. 10019, 287-295 (2016)

Thomas, J. ; Garzorz-Stark, N. ; Kuepper, L. ; Krause, L. ; Müller, N.S. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, K. ; Eyerich, S.

Characterization of multiple B cell subsets in peripheral blood of psoriasis patients identifies a correlation of plasma and regulatory B cells with disease severity.

Exp. Dermatol. 25, 27-28 (2016)

Lauffer, F. ; Krause, L. ; Franz, R. ; Garzorz-Stark, N. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

A distinct molecular signature of interface dermatitis as determined by gene expression analysis combined with disease independent histological phenotyping.

Exp. Dermatol. 25, 30-31 (2016)

Kuepper, M.K. ; Thomas, J. ; Garzorz-Stark, N. ; Krause, L. ; Müller, N.S. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, K. ; Eyerich, S.

Characterization of multiple B cell subsets in peripheral blood of psoriasis patients identifies a correlation of regulatory B cells and disease severity.

J. Invest. Dermatol. 136, S217-S217 (2016)

Lauffer, F. ; Krause, L. ; Franz, R. ; Garzorz-Stark, N. ; Biedermann, T. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

Interface dermatitis shows a distinctive molecular signature independent from individual disease background.

J. Invest. Dermatol. 136, S219-S219 (2016)

Kong, B. ; Bruns, P. ; Behler, N.A. ; Chang, L. ; Schlitter, A.M. ; Cao, J. ; Gewies, A. ; Ruland, J. ; Fritzsche, S. ; Valkovskaya, N. ; Jian, Z. ; Regel, I. ; Raulefs, S. ; Irmler, M. ; Beckers, J. ; Friess, H. ; Erkan, M. ; Müller, N.S. ; Roth, S. ; Hackert, T. ; Esposito, I. ; Theis, F.J. ; Kleeff, J. ; Michalski, C.W.

Dynamic landscape of pancreatic carcinogenesis reveals early molecular networks of malignancy.

Gut 67, 146-156 (2016)

Fiedler, A. ; Raeth, S. ; Theis, F.J. ; Hausser, A. ; Hasenauer, J.

Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

BMC Syst. Biol. 10:80 (2016)

Haghverdi, L. ; Büttner, M. ; Wolf, F.A. ; Buettner, F. ; Theis, F.J.

Diffusion pseudotime robustly reconstructs lineage branching.

Nat. Methods 13, 845-848 (2016)

Carpenter, A. ; Eddy, S.E. ; Flicek, P. ; Gymrek, M. ; Hammell, M. ; Jaqaman, K. ; Jenkins, J. ; Koller, D. ; Lappalainen, T. ; Oshlack, A. ; Shamir, R. ; Singh, M. ; Teichmann, S. ; Theis, F.J. ; Troyanskaya, O.

What is the key best practice for collaborating with a computational biologist?

Cell Syst. 3, 7-11 (2016)

Theis, F.J.

Zelle unter Beobachtung: "Mit der Software können wir die Entwicklung im Video studieren".

MEDICA Magazin, DOI: undefined (2016)

Fröhlich, F. ; Thomas, P. ; Kazeroonian, A. ; Theis, F.J. ; Grima, R. ; Hasenauer, J.

Inference for stochastic chemical kinetics using moment equations and system size expansion.

PLoS Comput. Biol. 12:e1005030 (2016)

Sacher, A. ; Theis, F.J.

Von lernfähigen Maschinen lernen.

Laborjournal 7-8, 59-61 (2016)

Much, D. ; Beyerlein, A. ; Kindt, A. ; Krumsiek, J. ; Stückler, F. ; Rossbauer, M. ; Hofelich, A. ; Wiesenäcker, D. ; Hivner, S. ; Herbst, M. ; Römisch-Margl, W. ; Prehn, C. ; Adamski, J. ; Kastenmüller, G. ; Theis, F.J. ; Ziegler, A.-G. ; Hummel, S.

Lactation is associated with altered metabolomic signatures in women with gestational diabetes.

Diabetologia 59, 2193-2202 (2016)

Hilsenbeck, O. ; Schwarzfischer, M. ; Skylaki, S. ; Schauberger, B. ; Hoppe, P.S. ; Loeffler, D. ; Kokkaliaris, K.D. ; Hastreiter, S. ; Skylaki, E. ; Filipczyk, A. ; Strasser, M. ; Buggenthin, F. ; Feigelman, J. ; Krumsiek, J. ; van den Berg, A.J. ; Endele, M. ; Etzrodt, M. ; Marr, C. ; Theis, F.J. ; Schroeder, T.

Software tools for single-cell tracking and quantification of cellular and molecular properties.

Nat. Biotechnol. 34, 703-706 (2016)

Hoppe, P.S. ; Schwarzfischer, M. ; Loeffler, D. ; Kokkaliaris, K.D. ; Hilsenbeck, O. ; Moritz, N. ; Endele, M. ; Filipczyk, A. ; Gambardella, A. ; Ahmed, N. ; Etzrodt, M. ; Coutu, D.L. ; Rieger, M.A. ; Marr, C. ; Strasser, M. ; Schauberger, B. ; Burtscher, I. ; Ermakova, O. ; Bürger, A. ; Lickert, H. ; Nerlov, C. ; Theis, F.J. ; Schroeder, T.

Early myeloid lineage choice is not initiated by random PU.1 to GATA1 protein ratios.

Nature 535, 299-302 (2016)

Scheel, C. ; Linnemann, J.R. ; Miura, H. ; Meixner, L.K. ; Irmier, M. ; Kloos, U.J. ; Hirschi, B. ; Bartsch, H.S. ; Sass, S. ; Beckers, J. ; Theis, F.J. ; Gabka, C. ; Sotlar, K.

A force-sensitive organoid assay to quantify regenerative potential of single primary human mammary cells.

Cancer Res. 76:P1-06-02 (2016)

Garzorz-Stark, N. ; Krause, L. ; Lauffer, F. ; Atenhan, A. ; Thomas, J. ; Stark, S.P. ; Franz, R. ; Weidinger, S. ; Balato, A. ; Müller, N.S. ; Theis, F.J. ; Ring, J. ; Schmidt-Weber, C.B. ; Biedermann, T. ; Eyerich, S. ; Eyerich, K.

A novel molecular disease classifier for psoriasis and eczema.

Exp. Dermatol. 25, 767-774 (2016)

Styczynski, M.P. ; Theis, F.J.

Systems biology - the intersection of experiments and computation, underpinning biotechnology.

Curr. Opin. Biotechnol. 39, IV-VI (2016)

Krause, L. ; Mourantchanian, V. ; Brockow, K. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Knapp, B. ; Müller, N.S. ; Eyerich, S.

A computational model to predict severity of atopic eczema from 30 serum proteins.

J. Allergy Clin. Immunol. 138, 1207-1210.e2 (2016)

Theis, F.J.

Das ist der Zyklus der Systembiologie.

Laborjournal 23, 22-25 (2016)

Krumsiek, J. ; Bartel, J. ; Theis, F.J.

Computational approaches for systems metabolomics.

Curr. Opin. Biotechnol. 39, 198-206 (2016)

Geissen, E.M. ; Hasenauer, J. ; Heinrich, S. ; Hauf, S. ; Theis, F.J. ; Radde, N.

MEMO - multi-experiment mixture model analysis of censored data.

Bioinformatics 32, 2464-2472 (2016)

Kondofersky, I. ; Theis, F.J. ; Fuchs, C.

Inferring catalysis in biological systems.

IET Syst. Biol. 10, 210-218 (2016)

Rolle-Kampczyk, U.E. ; Krumsiek, J. ; Otto, W. ; Röder, S.W. ; Kohajda, T. ; Borte, M. ; Theis, F.J. ; Lehmann, I. ; von Bergen, M.

Metabolomics reveals effects of maternal smoking on endogenous metabolites from lipid metabolism in cord blood of newborns.

Metabolomics 12:76 (2016)

Haffner, I. ; Luber, B. ; Maier, D. ; Geier, B. ; Theis, F.J. ; Meyer-Hermann, M. ; Walch, A.K. ; Kretzschmar, A.K. ; von Weikersthal, L.F. ; Knorrenschild, J.R. ; Schierle, K. ; Wittekind, C. ; Lordick, F.

Clinical validation of response and resistance factor candidates to targeted therapy in Gastric Cancer (GC).

Oncol. Res. Treat. 39, 16-17 (2016)

Preusse, M. ; Theis, F.J. ; Müller, N.S.

miTALOS v2: Analyzing tissue specific microRNA function.

PLoS ONE 11:e0151771 (2016)

Huypens, P. ; Sass, S. ; Wu, M. ; Dyckhoff, D. ; Tschöp, M.H. ; Theis, F.J. ; Marschall, S. ; Hrabě de Angelis, M. ; Beckers, J.

Epigenetic germline inheritance of diet-induced obesity and insulin resistance.

Nat. Genet. 48, 497-499 (2016)

Laimighofer, M. ; Krumsiek, J. ; Buettner, F. ; Theis, F.J.

Unbiased prediction and feature selection in high-dimensional survival regression.

J. Comput. Biol. 23, 279-290 (2016)

Kazeroonian, A. ; Fröhlich, F. ; Raue, A. ; Theis, F.J. ; Hasenauer, J.

CERENA: ChEmical REaction Network Analyzer - a toolbox for the simulation and analysis of stochastic chemical kinetics.

PLoS ONE 11:e0146732 (2016)

Jung, B. ; Padula, D. ; Burtscher, I. ; Landerer, C. ; Lutter, D. ; Theis, F.J. ; Messias, A.C. ; Geerlof, A. ; Sattler, M. ; Kremmer, E. ; Boldt, K. ; Ueffing, M. ; Lickert, H.

Pitchfork and Gprasp2 target smoothened to the primary cilium for Hedgehog pathway activation.

PLoS ONE 11:e0149477 (2016)

Stojcheva, N. ; Schechtmann, G. ; Sass, S. ; Roth, P. ; Florea, A.M. ; Stefanski, A. ; Stühler, K. ; Wolter, M. ; Müller, N.S. ; Theis, F.J. ; Weller, M.G. ; Reifenberger, G. ; Happold, C.

MicroRNA-138 promotes acquired alkylator resistance in glioblastoma by targeting the Bcl-2-interacting mediator BIM.

Oncotarget 7, 12937-12950 (2016)

Blasi, T. ; Feller, C. ; Feigelman, J. ; Hasenauer, J. ; Imhof, A. ; Theis, F.J. ; Becker, P.B. ; Marr, C.

Combinatorial histone acetylation patterns are generated by motif-specific reactions.

Cell Syst. 2, 49-58 (2016)

Blasi, T. ; Hennig, H. ; Summers, H.D. ; Theis, F.J. ; Cerveira, J. ; Patterson, J.O. ; Davies, D. ; Filby, A. ; Carpenter, A.E. ; Rees, P.

Label-free cell cycle analysis for high-throughput imaging flow cytometry.

Nat. Commun. 7:10256 (2016)

Hug, S. ; Schmidl, D. ; Li, W.B. ; Greiter, M. ; Theis, F.J.

Bayesian model selection methods and their application to biological ODE systems.

In: Geris, L.* ; Gomez-Cabrero, D.* [Eds.]: Uncertainty in Biology : A Computational Modeling Approach. Berlin; Heidelberg: Springer, 2016. 243-268 (Stud. Mechanobiol. Tiss. Engineering Biomater. ; 17)

Angerer, P. ; Haghverdi, L. ; Büttner, M. ; Theis, F.J. ; Marr, C. ; Buettner, F.

Destiny: Diffusion maps for large-scale single-cell data in R.

Bioinformatics 32, 1241-1243 (2016)

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The global gene expression profile of the secondary transition during pancreatic development.

Mech. Dev. 139, 51-64 (2016)

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Interleukin-4 and interferon-γ orchestrate an epithelial polarization in the airways.

Mucosal Immunol. 9, 917-926 (2016)

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Metabolomics screening identifies reduced L-carnitine to be associated with progressive emphysema.

Clin. Sci. 130, 273-287 (2016)

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Separation of uncorrelated stationary time series using autocovariance matrices.

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Kong, B. ; Wu, W. ; Cheng, T. ; Schlitter, A.M. ; Qian, C. ; Bruns, P. ; Jian, Z. ; Jager, C. ; Regel, I. ; Raulefs, S. ; Behler, N. ; Irmler, M. ; Beckers, J. ; Friess, H. ; Erkan, M. ; Siveke, J.T. ; Tannapfel, A. ; Hahn, S.A. ; Theis, F.J. ; Esposito, I. ; Kleeff, J. ; Michalski, C.W.

A subset of metastatic pancreatic ductal adenocarcinomas depends quantitatively on oncogenic Kras/Mek/Erk-induced hyperactive mTOR signalling.

Gut 65, 647-657 (2016)

Bartel, S. ; Schulz, N. ; Schamberger, A.C. ; Alessandrini, F. ; Pagel, P. ; Theis, F.J. ; Milger, K. ; Nößner, E. ; Stick, S.M. ; Kicic, A. ; Eickelberg, O. ; Freishtat, R.J. ; Krauss-Etschmann, S.

SEC14-like 3 is decreased in airway ciliated cells in experimental and paediatric asthma.

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Sass, S. ; Pitea, A. ; Unger, K. ; Hess, J. ; Müller, N.S. ; Theis, F.J.

MicroRNA-target network inference and local network enrichment analysis identify two microRNA clusters with distinct functions in head and neck squamous cell carcinoma.

Int. J. Mol. Sci. 16, 30204-30222 (2015)

Wang, L. ; Belagiannis, V. ; Marr, C. ; Theis, F.J. ; Yang, G.Z. ; Navab, N.

Anatomic-landmark detection using graphical context modelling.

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Approximate bayesian computation for stochastic single-cell time-lapse data using multivariate test statistics.

Lect. Notes Comput. Sc. 9308, 52-63 (2015)

Marr, C. ; Hasenauer, J. ; Theis, F.J.

Models and methods for systems biology and systems medicine: The Institute of Computational Biology at the Helmholtz Zentrum München.

Systembiologie.de 9, 40-43 (2015)

Preusse, M. ; Marr, C. ; Saunders, S. ; Maticzka, D. ; Lickert, H. ; Backofen, R. ; Theis, F.J.

SimiRa: A tool to identify coregulation between microRNAs and RNA-binding proteins.

RNA Biol. 12, 998-1009 (2015)

Filipczyk, A. ; Marr, C. ; Hastreiter, S. ; Feigelman, J. ; Schwarzfischer, M. ; Hoppe, P.S. ; Loeffler, D. ; Kokkaliaris, K.D. ; Endele, M. ; Schauberger, B. ; Hilsenbeck, O. ; Skylaki, S. ; Hasenauer, J. ; Anastassiadis, K. ; Theis, F.J. ; Schroeder, T.

Network plasticity of pluripotency transcription factors in embryonic stem cells.

Nat. Cell Biol. 17, 1235-1246 (2015)

Strasser, M. ; Feigelman, J. ; Theis, F.J. ; Marr, C.

Inference of spatiotemporal effects on cellular state transitions from time-lapse microscopy.

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Ilmonen, P. ; Nordhausen, K. ; Oja, H. ; Theis, F.J.

An affine equivariant robust second-order BSS method.

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Garzorz, N.V. ; Krause, L. ; Lauffer, F. ; Atenhan, A. ; Thomas, J. ; Theis, F.J. ; Biedermann, T. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

Molecular diagnostics of psoriasis and eczema-a novel approach to establish personalised therapy.

J. Invest. Dermatol. 135, S1 (2015)

Meyer, S.U. ; Sass, S. ; Müller, N.S. ; Krebs, S. ; Bauersachs, S. ; Kaiser, S. ; Blum, H. ; Thirion, C. ; Krause, S. ; Theis, F.J. ; Pfaffl, M.W.

Integrative analysis of MicroRNA and mRNA data reveals an orchestrated function of MicroRNAs in skeletal myocyte differentiation in response to TNF-α or IGF1.

PLoS ONE 10:e0135284 (2015)

Krumsiek, J. ; Mittelstraß, K. ; Do, K.T. ; Stückler, F. ; Ried, J.S. ; Adamski, J. ; Peters, A. ; Illig, T. ; Kronenberg, F. ; Friedrich, N. ; Nauck, M. ; Pietzner, M. ; Mook-Kanamori, D.O. ; Suhre, K. ; Gieger, C. ; Grallert, H. ; Theis, F.J. ; Kastenmüller, G.

Gender-specific pathway differences in the human serum metabolome.

Metabolomics 11, 1815-1833 (2015)

Müller, S. ; Raulefs, S. ; Bruns, P. ; Afonso-Grunz, F. ; Plötner, A. ; Thermann, R. ; Jager, C. ; Schlitter, A.M. ; Kong, B. ; Regel, I. ; Roth, W.K. ; Rotter, B. ; Hoffmeier, K. ; Kahl, G.F. ; Koch, I. ; Theis, F.J. ; Kleeff, J. ; Winter, P. ; Michalski, C.W.

Erratum to: Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer.

Mol. Cancer 14:144 (2015)

Raue, A. ; Steiert, B. ; Schelker, M. ; Kreutz, C. ; Maiwald, T. ; Hass, H. ; Vanlier, J. ; Tönsing, C. ; Adlung, L. ; Engesser, R. ; Mader, W. ; Heinemann, T. ; Hasenauer, J. ; Schilling, M. ; Höfer, T. ; Klipp, E. ; Theis, F.J. ; Klingmüller, U. ; Schöberl, B. ; Timmer, J.

Data2Dynamics: A modeling environment tailored to parameter estimation in dynamical systems.

Bioinformatics 31, 3558-3560 (2015)

Hasenauer, J. ; Jagiella, N. ; Hross, S. ; Theis, F.J.

Data-driven modelling of biological multi-scale processes.

J. Coupled Syst. Multiscale Dyn. 3, 101-121 (2015)

Masserdotti, G. ; Gillotin, S. ; Sutor, B. ; Drechsel, D. ; Irmler, M. ; Jørgensen, H.F. ; Sass, S. ; Theis, F.J. ; Beckers, J. ; Berninger, B. ; Guillemot, F. ; Götz, M.

Transcriptional mechanisms of proneural factors and REST in regulating neuronal reprogramming of astrocytes.

Cell Stem Cell 17, 74-88 (2015)

Bartel, J. ; Krumsiek, J. ; Schramm, K. ; Adamski, J. ; Gieger, C. ; Herder, C. ; Carstensen, M. ; Peters, A. ; Rathmann, W. ; Roden, M. ; Strauch, K. ; Suhre, K. ; Kastenmüller, G. ; Prokisch, H. ; Theis, F.J.

The human blood metabolome-transcriptome interface.

PLoS Genet. 11:e1005274 (2015)

Ocone, A. ; Haghverdi, L. ; Müller, N.S. ; Theis, F.J.

Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data.

Bioinformatics 31, i89-i96 (2015)

Linnemann, J. ; Miura, H. ; Meixner, L.K. ; Irmler, M. ; Kloos, U. ; Hirschi, B. ; Bartsch, H.S. ; Sass, S. ; Beckers, J. ; Theis, F.J. ; Gabka, C. ; Sotlar, K. ; Scheel, C.

Quantification of regenerative potential in primary human mammary epithelial cells.

Development 142, 3239-3251 (2015)

Sadic, D. ; Schmidt, K. ; Groh, S. ; Kondofersky, I. ; Ellwart, J.W. ; Fuchs, C. ; Theis, F.J. ; Schotta, G.

Atrx promotes heterochromatin formation at retrotransposons.

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Wilson, N.K. ; Kent, D.G. ; Buettner, F. ; Shehata, M. ; Macaulay, I.C. ; Calero-Nieto, F.J. ; Sánchez Castillo, M. ; Oedekoven, C.A. ; Diamanti, E. ; Schulte, R. ; Ponting, C.P. ; Voet, T. ; Caldas, C. ; Stingl, J. ; Green, A.R. ; Theis, F.J. ; Göttgens, B.

Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations.

Cell Stem Cell 16, 712-724 (2015)

Haghverdi, L. ; Buettner, F. ; Theis, F.J.

Diffusion maps for high-dimensional single-cell analysis of differentiation data.

Bioinformatics 31, 2989-2998 (2015)

Barbosa, J.S. ; Sanchez-Gonzalez, R. ; di Giaimo, R. ; Baumgart, E.V. ; Theis, F.J. ; Götz, M. ; Ninkovic, J.

Live imaging of adult neural stem cell behavior in the intact and injured zebrafish brain.

Science 348, 789-793 (2015)

Kondofersky, I. ; Fuchs, C. ; Theis, F.J.

Identifying latent dynamic components in biological systems.

IET Syst. Biol. 9, 193-203 (2015)

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Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer.

Mol. Cancer 14:94 (2015)

Helmbrecht, M.S. ; Soellner, H. ; Castiblanco-Urbina, M.A. ; Winzeck, S. ; Sundermeier, J. ; Theis, F.J. ; Fouad, K. ; Huber, A.B.

A critical period for postnatal adaptive plasticity in a model of motor axon miswiring.

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Theis, F.J. ; Ugelvig, L.V. ; Marr, C. ; Cremer, S.

Opposing effects of allogrooming on disease transmission in ant societies.

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Multi-omic signature of body weight change: Results from a population-based cohort study.

BMC Med. 13:48 (2015)

Hug, S. ; Schwarzfischer, M. ; Hasenauer, J. ; Marr, C. ; Theis, F.J.

An adaptive scheduling scheme for calculating Bayes factors with thermodynamic integration using Simpson’s rule.

Stat. Comp. 26, 663-677 (2015)

Calzolari, F. ; Michel, J. ; Baumgart, E.V. ; Theis, F.J. ; Götz, M. ; Ninkovic, J.

Fast clonal expansion and limited neural stem cell self-renewal in the adult subependymal zone.

Nat. Neurosci. 18, 490-492 (2015)

Moignard, V. ; Woodhouse, S. ; Haghverdi, L. ; Lilly, A.J. ; Tanaka, Y. ; Wilkinson, A.C. ; Buettner, F. ; Macaulay, I.C. ; Jawaid, W. ; Diamanti, E. ; Nishikawa, S.I. ; Piterman, N. ; Kouskoff, V. ; Theis, F.J. ; Fisher, J. ; Gottgens, B.

Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Nat. Biotechnol. 33, 269-276 (2015)

Illner, K. ; Miettinen, J. ; Fuchs, C. ; Taskinen, S. ; Nordhausen, K. ; Oja, H. ; Theis, F.J.

Model selection using limiting distributions of second-order blind source separation algorithms.

Signal Process. 113, 95-103 (2015)

Kong, B. ; Bruns, P. ; Raulefs, S. ; Rieder, S. ; Paul, L. ; da Costa, O.P. ; Buch, T. ; Theis, F.J. ; Michalski, C.W. ; Kleeff, J.

Metabolism gene signatures and surgical site infections in abdominal surgery.

Int. J. Surg. 14, 67-74 (2015)

Buettner, F. ; Natarajan, K.N. ; Casale, F.P. ; Proserpio, V. ; Scialdone, A. ; Theis, F.J. ; Teichmann, S.A. ; Marioni, J.C. ; Stegle, O.

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

Nat. Biotechnol. 33, 155-160 (2015)

Schmidt, J. ; Panzilius, E. ; Bartsch, H.S. ; Irmler, M. ; Beckers, J. ; Kari, V. ; Linnemann, J. ; Dragoi, D. ; Hirschi, B. ; Kloos, U. ; Sass, S. ; Theis, F.J. ; Kahlert, S. ; Johnsen, S.A. ; Sotlar, K. ; Scheel, C.

Stem-cell-like properties and epithelial plasticity arise as stable traits after transient Twist1 activation.

Cell Rep. 10, 131-139 (2015)

Do, K.T. ; Kastenmüller, G. ; Mook-Kanamori, D.O. ; Yousri, N.A. ; Theis, F.J. ; Suhre, K. ; Krumsiek, J.

Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva.

J. Proteome Res. 14, 1183-1194 (2015)

Sass, S. ; Buettner, F. ; Müller, N.S. ; Theis, F.J.

RAMONA: A web application for gene set analysis on multilevel omics data.

Bioinformatics 31, 128-130 (2015)

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Modeling of stochastic biological processes with non-polynomial propensities using non-central conditional moment equation.

IFAC PapersOnline 19, 1729-1735 (2014)

Reversat, A. ; Buggenthin, F. ; Merrin, J. ; Leithner, A. ; de Vries, I. ; Theis, F.J. ; Marr, C. ; Sixt, M.

Morphodynamic analysis of T lymphocyte migration in confined microenvironments.

Mol. Biol. Cell 25:P537 (2014)

Quaranta, M. ; Knapp, B. ; Garzoz, N. ; Mattii, M. ; Pullabhatla, V. ; Pennino, D. ; Andres, C. ; Traidl-Hoffmann, C. ; Cavani, A. ; Theis, F.J. ; Ring, J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Eyerich, K.

Intraindividual genome expression analysis reveals opposing immune reaction in psoriasis and eczema.

Br. J. Dermatol. 171, E135 (2014)

Fröhlich, F. ; Theis, F.J. ; Hasenauer, J.

Uncertainty analysis for non-identifiable dynamical systems: Profile likelihoods, bootstrapping and more.

Lect. Notes Comput. Sc. 8859, 61-72 (2014)

Fröhlich, F. ; Hross, S. ; Theis, F.J. ; Hasenauer, J.

Radial basis function approximations of Bayesian parameter posterior densities for uncertainty analysis.

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Winkler, C. ; Krumsiek, J. ; Buettner, F. ; Angermüller, C. ; Giannopoulou, E.Z. ; Theis, F.J. ; Ziegler, A.-G. ; Bonifacio, E.

Erratum to: Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes.

Diabetologia 58, 206 (2014)

Waldera-Lupa, D.M. ; Kalfalah, F. ; Florea, A.M. ; Sass, S. ; Kruse, F.E. ; Rieder, V. ; Tigges, J. ; Fritsche, E. ; Krutmann, J. ; Busch, H. ; Boerries, M. ; Meyer, H.E. ; Boege, F. ; Theis, F.J. ; Reifenberger, G. ; Stühler, K.

Proteome-wide analysis reveals an age-associated cellular phenotype of in situ aged human fibroblasts.

Aging 6, 856-878 (2014)

Khakhutskyy, V. ; Schwarzfischer, M. ; Hubig, N. ; Plant, C. ; Marr, C. ; Rieger, M.A. ; Schröder, T. ; Theis, F.J.

Centroid clustering of cellular lineage trees.

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Illner, K. ; Fuchs, C. ; Theis, F.J.

Bayesian blind source separation applied to the lymphocyte pathway.

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Single-cell analysis: Biology at high resolution.

Sep. Sci. Appl. 34, 24-26 (2014)

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Einzelzellanalysen: Biologie in Hochauflösung.

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Bayesian blind source separation for data with network structure.

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miR-23a-3p causes cellular senescence by targeting hyaluronan synthase2: Possible implication for skin aging.

J. Invest. Dermatol. 135, 369-377 (2014)

Bartel, S. ; Schulz, N. ; Alessandrini, F. ; Theis, F.J. ; Eickelberg, O. ; Kicic, A. ; Freishtat, R.J. ; Krauss-Etschmann, S.

MicroRNA-based identification of epithelial SEC14L3 loss in experimental and human paediatric asthma.

Allergy 69, 40-41 (2014)

Winkler, C. ; Krumsiek, J. ; Buettner, F. ; Angermüller, C. ; Giannopoulou, E.Z. ; Theis, F.J. ; Ziegler, A.-G. ; Bonifacio, E.

Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes.

Diabetologia 57, 2521-2529 (2014)

Matthes, M. ; Preusse, M. ; Zhang, J. ; Schechter, J. ; Mayer, D. ; Lentes, B. ; Theis, F.J. ; Prakash, N. ; Wurst, W. ; Trümbach, D.

Mouse IDGenes: A reference database for genetic interactions in the developing mouse brain.

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Cytokine-regulated GADD45G induces differentiation and lineage selection in hematopoietic stem cells.

Exp. Hematol. 42, S57 (2014)

Moignard, V. ; Woodhouse, S. ; Haghverdi, L. ; Lilly, J. ; Tanaka, Y. ; Wilkinson, A. ; Buettner, F. ; Nishikawa, S. ; Piterman, N. ; Kouskoff, V. ; Theis, F.J. ; Fisher, J. ; Göttgens, B.

Decoding the transcriptional program for blood development from whole tissue single-cell gene expression measurements.

Exp. Hematol. 42, S52 (2014)

Vinnikov, I.A. ; Hajdukiewicz, K. ; Reymann, J. ; Beneke, J. ; Czajkowski, R. ; Roth, L.C. ; Novak, M. ; Roller, A. ; Dörner, N. ; Starkuviene, V. ; Theis, F.J. ; Erfle, H. ; Schütz, G. ; Grinevich, V. ; Konopka, W.

Hypothalamic miR-103 protects from hyperphagic obesity in mice.

J. Neurosci. 34, 10659-10674 (2014)

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Eczema ≠ eczema: The transcriptional heterogeneity of eczema.

Br. J. Dermatol. 170, E19 (2014)

Quaranta, M. ; Eyerich, S. ; Knapp, B. ; Nasorri, F. ; Scarponi, C. ; Mattii, M. ; Garzorz-Stark, N. ; Harlfinger, A.T. ; Jaeger, T. ; Grosber, M. ; Pennino, D. ; Mempel, M. ; Schnopp, C. ; Theis, F.J. ; Albanesi, C. ; Cavani, A. ; Schmidt-Weber, C.B. ; Ring, J. ; Eyerich, K.

Allergic contact dermatitis in psoriasis patients: Typical, delayed, and non-interacting.

PLoS ONE 9:e101814 (2014)

Feigelman, J. ; Theis, F.J. ; Marr, C.

MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data.

BMC Bioinformatics 15:240 (2014)

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Intraindividual genome expression analysis reveals a specific molecular signature of psoriasis and eczema.

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Intra-individual genome expression analysis reveals a specific molecular signature of psoriasis and eczema.

J. Invest. Dermatol. 134, S1 (2014)

Hasenauer, J. ; Hasenauer, C. ; Hucho, T. ; Theis, F.J.

ODE constrained mixture modelling: A method for unraveling subpopulation structures and dynamics.

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Cytokine-regulated GADD45G induces differentiation and lineage selection in hematopoietic stem cells.

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Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses.

Hum. Mol. Genet. 23, 5847-5857 (2014)

Meyer, S.U. ; Stoecker, K. ; Sass, S. ; Theis, F.J. ; Pfaffl, M.W.

Posttranscriptional regulatory networks: From expression profiling to integrative analysis of mRNA and microRNA data.

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An atlas of genetic influences on human blood metabolites.

Nat. Genet. 46, 543-550 (2014)

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Probabilistic PCA of censored data: Accounting for uncertainties in the visualisation of high-throughput single-cell qPCR data.

Bioinformatics 30, 1867-1875 (2014)

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Subtoxic concentrations of benzo[a]pyrene induce metabolic changes and oxidative stress in non-activated and affect the mTOR pathway in activated Jurkat T cells.

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miR-335 promotes mesendodermal lineage segregation and shapes a transcription factor gradient in the endoderm.

Development 141, 514-525 (2014)

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Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles.

Proc. Natl. Acad. Sci. U.S.A. 111, E626-E635 (2014)

Bonifacio, E. ; Krumsiek, J. ; Winkler, C. ; Theis, F.J. ; Ziegler, A.-G.

A strategy to find gene combinations that identify children who progress rapidly to type 1 diabetes after islet autoantibody seroconversion.

Acta Diabetol. 51, 403-411 (2014)

Hasenauer, J. ; Wolf, V. ; Kazeroonian, A. ; Theis, F.J.

Method of conditional moments (MCM) for the chemical master equation: A unified framework for the method of moments and hybrid stochastic-deterministic models.

J. Math. Biol. 69, 687-735 (2014)

Albrecht, E. ; Waldenberger, M. ; Krumsiek, J. ; Evans, A.M. ; Jeratsch, U. ; Breier, M. ; Adamski, J. ; Koenig, W. ; Zeilinger, S. ; Fuchs, C. ; Klopp, N. ; Theis, F.J. ; Wichmann, H.-E. ; Suhre, K. ; Illig, T. ; Strauch, K. ; Peters, A. ; Gieger, C. ; Kastenmüller, G. ; Döring, A. ; Meisinger, C.

Metabolite profiling reveals new insights into the regulation of serum urate in humans.

Metabolomics 10, 141-151 (2014)

Kong, B. ; Wu, W. ; Cheng, T. ; Schlitter, A.M. ; Bruns, P. ; Jaeger, C. ; Regel, I. ; Raulefs, S. ; Behler, N. ; Irmler, M. ; Beckers, J. ; Erkan, M. ; Theis, F.J. ; Esposito, I. ; Kleeff, J. ; Michalski, C.W.

Identification and characterization of an Aldh1a3-positive subtype of pancreatic ductal adenocarcinoma mediated by oncogenic Krasg12d/Erk-Mtor axis.

Pancreas 42, 1360-1361 (2013)

Kong, B. ; Behler, N. ; Bruns, P. ; Schlitter, A.M. ; Valkovska, N. ; Fritzsche, S. ; Raulefs, S. ; Regel, I. ; Erkan, M. ; Theis, F.J. ; Esposito, I. ; Kleeff, J. ; Michalski, C.W.

Pancreatic progenitor expansion, mesenchymal cell proliferation and inflammation are required during early carcinogenesis.

Pancreas 42, 1360 (2013)

Kuruoglu, E.E. ; Theis, F.J.

Dependent component analysis.

EURASIP J. Adv. Signal Process. 2013:185 (2013)

Vehlow, C. ; Hasenauer, J. ; Krämer, A. ; Raue, A. ; Hug, S. ; Timmer, J. ; Radde, N. ; Theis, F.J. ; Weiskopf, D.

iVUN: Interactive Visualization of Uncertain biochemical reaction Networks.

BMC Bioinformatics 14:S2 (2013)

Bartel, S. ; Schulz, N. ; Theis, F.J. ; Alessandrini, F. ; Takenaka, S. ; Eickelberg, O. ; Krauss-Etschmann, S.

SEC14L3 is de-regulated in murine experimental asthma via miRNA-mediated down-regulation of CREB.

Allergy 68, 233-233 (2013)

Bartel, J. ; Krumsiek, J. ; Theis, F.J.

Statistical methods for the analysis of high-throughput metabolomics data.

Comp. Struc. Biotech. J. 4:e201301009 (2013)

Kazeroonian, A. ; Hasenauer, J. ; Theis, F.J.

Parameter estimation for stochastic biochemical processes: A comparison of moment equation and fintie state projection.

In: Autio, R.* ; Shmulevich, I.* ; Strimmer, K.* ; Wiuf, C.* ; Sarbu, S.* ; Yli-Harja, O.* [Eds.]: Proceedings of the WCSB 2013 (10th International Workshop on Computational Systems Biology, 10 - 12 June 2013, Tampere, Finland). Tampere: Tampere International Center for Signal Processing, 2013. 66-73 (TICSP Series ; 63)

Sass, S. ; Buettner, F. ; Müller, N.S. ; Theis, F.J.

A modular framework for gene set analysis integrating multilevel omics data.

Nucleic Acids Res. 41, 9622-9633 (2013)

Buggenthin, F. ; Marr, C. ; Schwarzfischer, M. ; Hoppe, P.S. ; Hilsenbeck, O. ; Schroeder, T. ; Theis, F.J.

An automatic method for robust and fast cell detection in bright field images from high-throughput microscopy.

BMC Bioinformatics 14:297 (2013)

Raue, A. ; Schilling, M. ; Bachmann, J. ; Matteson, A. ; Schelker, M. ; Kaschek, D. ; Hug, S. ; Kreutz, C. ; Harms, B.D. ; Theis, F.J. ; Klingmüller, U. ; Timmer, J.

Lessons learned from quantitative dynamical modeling in systems biology.

PLoS ONE 8:e74335 (2013)

Bartel, S. ; Schulz, N. ; Theis, F.J. ; Alessandrini, F. ; Takenaka, S. ; Eickelberg, O. ; Krauss-Etschmann, S.

miRNA-based identification of SEC14L3 deregulation in murine experimental asthma.

Eur. Respir. J. 42 (2013)

Hock, S. ; Hasenauer, J. ; Theis, F.J.

Modeling of 2D diffusion processes based on microscopy data: Parameter estimation and practical identifiability analysis.

BMC Bioinformatics 14:S7 (2013)

Andres, C. ; Hasenauer, J. ; Ahn, H.S. ; Joseph, E.K. ; Isensee, J. ; Theis, F.J. ; Allgöwer, F. ; Levine, J.D. ; Dib-Hajj, S.D. ; Waxman, S.G. ; Hucho, T.

Wound-healing growth factor, basic FGF, induces Erk1/2-dependent mechanical hyperalgesia.

Pain 154, 2216-2226 (2013)

Rinck, A. ; Preusse, M. ; Laggerbauer, B. ; Lickert, H. ; Engelhardt, S. ; Theis, F.J.

The human transcriptome is enriched for miRNA-binding sites located in cooperativity-permitting distance.

RNA Biol. 10, 1125-1135 (2013)

Hock, S. ; Ng, Y.K. ; Hasenauer, J. ; Wittmann, D.M. ; Lutter, D. ; Trümbach, D. ; Wurst, W. ; Prakash, N. ; Theis, F.J.

Sharpening of expression domains induced by transcription and microRNA regulation within a spatio-temporal model of mid-hindbrain boundary formation.

BMC Syst. Biol. 7:48 (2013)

Hug, S. ; Raue, A. ; Hasenauer, J. ; Bachmann, J. ; Klingmüller, U. ; Timmer, J. ; Theis, F.J.

High-dimensional Bayesian parameter estimation: Case study for a model of JAK2/STAT5 signaling.

Math. Biosci. 246, 293-304 (2013)

Schmidl, D. ; Czado, C. ; Hug, S. ; Theis, F.J.

A vine-copula based adaptive MCMC sampler for efficient inference of dynamical systems.

Bayesian Anal. 8, 1-22 (2013)

Schmidl, D. ; Czado, C. ; Hug, S. ; Theis, F.J.

Rejoinder on "A vine-copula based adaptive MCMC sampler for efficient inference of dynamical systems".

Bayesian Anal. 8, 33-42 (2013)

Wittmann, D.M. ; Hock, S. ; Theis, F.J.

Truth-content and phase transitions of random boolean networks with generic logics.

SIAM J. Appl. Dyn. Syst. 12, 315-351 (2013)

Rickert, D. ; Fricker, N. ; Lavrik, I.N. ; Theis, F.J.

Systematic complexity reduction of signaling models and application to a CD95 signaling model for apoptosis.

In: Lavrik, I.N.* [Eds.]: Systems Biology of Apoptosis. New York: Springer, 2013. 57-84

Moignard, V. ; Macaulay, I.C. ; Swiers, G. ; Buettner, F. ; Schütte, J. ; Calero-Nieto, F.J. ; Kinston, S. ; Joshi, A. ; Hannah, R. ; Theis, F.J. ; Jacobsen, S.E. ; de Bruijn, M.F. ; Göttgens, B.

Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis.

Nat. Cell Biol. 15, 363-372 (2013)

Bardehle, S. ; Krüger, M. ; Buggenthin, F. ; Schwausch, J. ; Ninkovic, J. ; Clevers, H. ; Snippert, H.J. ; Theis, F.J. ; Meyer-Luehmann, M. ; Bechmann, I. ; Dimou, L. ; Götz, M.

Live imaging of astrocyte responses to acute injury reveals selective juxtavascular proliferation.

Nat. Neurosci. 16, 580-586 (2013)

Vehlow, C. ; Hasenauer, J. ; Theis, F.J. ; Weiskopf, D.

Visualizing edge-edge relations in graphs.

In: Proceedings of the 6th IEEE Pacific Visualization Symposium (IEEE PacificVis 2013 : 27.02.-01.03.2013, Sydney, Australia). Sydney, Australia: Univ. Sydney, 2013. 201-208

Ried, J.S. ; Baurecht, H. ; Stückler, F. ; Krumsiek, J. ; Gieger, C. ; Heinrich, J. ; Kabesch, M. ; Prehn, C. ; Peters, A. ; Rodriguez, E. ; Schulz, H. ; Strauch, K. ; Suhre, K. ; Wang-Sattler, R. ; Wichmann, H.-E. ; Theis, F.J. ; Illig, T. ; Adamski, J. ; Weidinger, S.

Integrative genetic and metabolite profiling analysis suggests altered phosphatidylcholine metabolism in asthma.

Allergy 68, 629-636 (2013)

Xu, T. ; Holzapfel, C. ; Dong, X. ; Bader, E. ; Yu, Z. ; Prehn, C. ; Perstorfer, K. ; Jaremek, M. ; Römisch-Margl, W. ; Rathmann, W. ; Li, Y. ; Wichmann, H.-E. ; Wallaschofski, H. ; Ladwig, K.-H. ; Theis, F.J. ; Suhre, K. ; Adamski, J. ; Illig, T. ; Peters, A. ; Wang-Sattler, R.

Effects of smoking and smoking cessation on human serum metabolite profile: Results from the KORA cohort study.

BMC Med. 11:60 (2013)

Köttgen, A. ; Albrecht, E. ; Teumer, A. ; Vitart, V. ; Krumsiek, J. ; Hundertmark, C. ; Pistis, G. ; Ruggiero, D. ; O'Seaghdha, C.M. ; Haller, T. ; Yang, Q. ; Tanaka, T. ; Johnson, A.D. ; Kutalik, Z. ; Smith, A.V. ; Shi, J. ; Struchalin, M. ; Middelberg, R.P. ; Brown, M.J. ; Gaffo, A.L. ; Pirastu, N. ; Li, G. ; Hayward, C. ; Zemunik, T. ; Huffman, J. ; Yengo, L. ; Zhao, J.H. ; Demirkan, A. ; Feitosa, M.F. ; Liu, X. ; Malerba, G. ; Lopez, L.M. ; van der Harst, P. ; Li, X. ; Kleber, M.E. ; Hicks, A.A. ; Nolte, I.M. ; Johansson, A. ; Murgia, F. ; Wild, S.H. ; Bakker, S.J. ; Peden, J.F. ; Dehghan, A. ; Steri, M. ; Tenesa, A. ; Lagou, V. ; Salo, P. ; Mangino, M. ; Rose, L.M. ; Lehtimäki, T. ; Woodward, O.M. ; Okada, Y. ; Tin, A. ; Müller, C. ; Oldmeadow, C. ; Putku, M. ; Czamara, D. ; Kraft, P. ; Frogheri, L. ; Thun, G.A. ; Grotevendt, A. ; Gislason, G.K. ; Harris, T.B. ; Launer, L.J. ; McArdle, P. ; Shuldiner, A.R. ; Boerwinkle, E. ; Coresh, J. ; Schmidt, H. ; Schallert, M. ; Martin, N.G. ; Montgomery, G.W. ; Kubo, M. ; Nakamura, Y. ; Munroe, P.B. ; Samani, N.J. ; Jacobs, D.R. J.r. ; Liu, K. ; D'Adamo, P. ; Ulivi, S. ; Rotter, J.I. ; Psaty, B.M. ; Vollenweider, P. ; Waeber, G. ; Campbell, S. ; Devuyst, O. ; Navarro, P. ; Kolcic, I. ; Hastie, N. ; Balkau, B. ; Froguel, P. ; Esko, T. ; Salumets, A. ; Khaw, K.T. ; Langenberg, C. ; Wareham, N.J. ; Isaacs, A. ; Kraja, A. ; Zhang, Q. ; Wild, P.S. ; Scott, R.J. ; Holliday, E.G. ; Org, E. ; Viigimaa, M. ; Bandinelli, S. ; Metter, J.E. ; Lupo, A. ; Trabetti, E. ; Sorice, R. ; Döring, A. ; Lattka, E. ; Strauch, K. ; Theis, F.J. ; Waldenberger, M. ; Wichmann, H.-E. ; Davies, G. ; Gow, A.J. ; Bruinenberg, M. ; LifeLines Cohort Study () ; Stolk, R.P. ; Kooner, J.S. ; Zhang, W. ; Winkelmann, B.R. ; Boehm, B.O. ; Lucae, S. ; Penninx, B.W. ; Smit, J.H. ; Curhan, G. ; Mudgal, P. ; Plenge, R.M. ; Portas, L. ; Persico, I. ; Kirin, M. ; Wilson, J.F. ; Leach, I.M. ; van Gilst, W.H. ; Goel, A. ; Ongen, H. ; Hofman, A. ; Rivadeneira, F. ; Uitterlinden, A.G. ; Imboden, M. ; von Eckardstein, A. ; Cucca, F. ; Nagaraja, R. ; Piras, M.G. ; Nauck, M. ; Schurmann, C. ; Budde, K. ; Ernst, F. ; Farrington, S.M. ; Theodoratou, E. ; Prokopenko, I. ; Stumvoll, M. ; Jula, A. ; Perola, M. ; Salomaa, V. ; Shin, S.Y. ; Spector, T.D. ; Sala, C. ; Ridker, P.M. ; Kähönen, M. ; Viikari, J. ; Hengstenberg, C. ; Nelson, C.P. ; Gieger, C. ; CARDIoGRAM Consortium (Wichmann, H.-E. ; Illig, T. ; Döring, A. ; Meisinger, C. ; Klopp, N. ; Peters, A. ; Meitinger, T.) ; DIAGRAM Consortium (Huth, C. ; Thorand, B. ; Meitinger, T. ; Gieger, C. ; Klopp, N. ; Grallert, H. ; Wichmann, H.-E. ; Illig, T. ; Petersen, A.-K.) ; ICBP Consortium () ; MAGIC Investigators (Wichmann, H.-E. ; Illig, T. ; Meisinger, C. ; Gieger, C. ; Thorand, B. ; Grallert, H.) ; Meschia, J.F. ; Nalls, M.A. ; Sharma, P. ; Singleton, A.B. ; Kamatani, N. ; Zeller, T. ; Burnier, M. ; Attia, J. ; Laan, M. ; Klopp, N. ; Hillege, H.L. ; Kloiber, S. ; Choi, H. ; Pirastu, M. ; Tore, S. ; Probst-Hensch, N.M. ; Völzke, H. ; Gudnason, V. ; Parsa, A. ; Schmidt, R. ; Whitfield, J.B. ; Fornage, M. ; Gasparini, P. ; Siscovick, D.S. ; Polasek, O. ; Campbell, H. ; Rudan, I. ; Bouatia-Naji, N. ; Metspalu, A. ; Loos, R.J. ; van Duijn, C.M. ; Borecki, I.B. ; Ferrucci, L. ; Gambaro, G. ; Deary, I.J. ; Wolffenbuttel, B.H. ; Chambers, J.C. ; Marz, W. ; Pramstaller, P.P. ; Snieder, H. ; Gyllensten, U. ; Wright, A.F. ; Navis, G. ; Watkins, H. ; Witteman, J.C. ; Sanna, S. ; Schipf, S. ; Dunlop, M.G. ; Tönjes, A. ; Ripatti, S. ; Soranzo, N. ; Toniolo, D. ; Chasman, D.I. ; Raitakari, O. ; Kao, W.H. ; Ciullo, M. ; Fox, C.S. ; Caulfield, M. ; Bochud, M.

Genome-wide association analyses identify 18 new loci associated with serum urate concentrations.

Nat. Genet. 45, 145-154 (2013)

Altmaier, E. ; Emeny, R.T. ; Krumsiek, J. ; Lacruz, M.E. ; Lukaschek, K. ; Häfner, S. ; Kastenmüller, G. ; Römisch-Margl, W. ; Prehn, C. ; Mohney, R.P. ; Evans, A.M. ; Milburn, M.V. ; Illig, T. ; Adamski, J. ; Theis, F.J. ; Suhre, K. ; Ladwig, K.-H.

Metabolomic profiles in individuals with negative affectivity and social inhibition: A population-based study of Type D personality.

Psychoneuroendocrinology 38, 1299-1309 (2013)

Raue, A. ; Kreutz, C. ; Theis, F.J. ; Timmer, J.

Joining forces of Bayesian and frequentist methodology: A study for inference in the presence of non-identiability.

Philos. Trans. R. Soc. A - Math. Phys. Eng. Sci. 371:20110544 (2013)

Cichocki, A. ; Theis, F.J. ; Yeredor, A. ; Zibulevsky, M.

Preface.

Lect. Notes Comput. Sc. 7191, V-VII (2012)

Gutch, H.W. ; Gruber, P. ; Yeredor, A. ; Theis, F.J.

ICA over finite fields - separability and algorithms.

Signal Process. 92, 1796-1808 (2012)

Ruepp, A. ; Kowarsch, A. ; Theis, F.J.

PhenomiR: MicroRNAs in human diseases and biological processes.

Methods Mol. Biol. 822, 249-260 (2012)

Nordhausen, K. ; Gutch, H.W. ; Oja, H. ; Theis, F.J.

Joint diagonalization of several scatter matrices for ICA.

In: Theis, F.J. ; Cichocki, A.* ; Yeredor, A* ; Zibulevsky, M.* [Eds.]: Proceedings (10th international conference on Latent Variable Analysis and Signal Separation). Heidelberg: Springer, 2012. 172-179 (Lecture Notes in Computer Science ; 7191)

Chursov, A. ; Kopetzky, S.J. ; Leshchiner, I. ; Kondofersky, I. ; Theis, F.J. ; Frishman, D. ; Shneider, A.

Specific temperature-induced perturbations of secondary mRNA structures are associated with the cold-adapted temperature-sensitive phenotype of influenza A virus.

RNA Biol. 9, 1266-1274 (2012)

Gutch, H.W. ; Theis, F.J.

To infinity and beyond: On ICA over Hilbert Spaces.

In: Theis, F.J. ; Cichocki, A.* ; Yeredor, A* ; Zibulevsky, M.* [Eds.]: Proceedings (10th International Conference, LVA/ICA 2012, 12-15 March 2012, Tel Aviv, Israel). Heidelberg: Springer, 2012. 180-187 (Lect. Notes Comput. Sc. ; 7191)

Plant, C.C. ; Mai Thai, S. ; Shao, J. ; Theis, F.J. ; Meyer-Bäse, A. ; Böhm, C.

Measuring non-Gaussianity by phi-transformed and fuzzy histograms.

Adv. Artif. Neural Syst. 2012:962105 (2012)

Krumsiek, J. ; Stückler, F. ; Kastenmüller, G. ; Theis, F.J.

Systems biology meets metabolism.

In: Suhre, K.* [Eds.]: Genetics Meets Metabolomics: from Experiment to Systems Biology. New York: Springer, 2012. 281-313

Winkler, C. ; Krumsiek, J. ; Lempainen, J. ; Achenbach, P. ; Grallert, H. ; Giannopoulou, E.Z. ; Bunk, M. ; Theis, F.J. ; Bonifacio, E. ; Ziegler, A.-G.

A strategy for combining minor genetic susceptibility genes to improve prediction of disease in type 1 diabetes.

Genes Immun. 13, 549-555 (2012)

Krumsiek, J. ; Suhre, K. ; Evans, A.M. ; Mitchell, M.W. ; Mohney, R.P. ; Milburn, M.V. ; Wägele, B. ; Römisch-Margl, W. ; Illig, T. ; Adamski, J. ; Gieger, C. ; Theis, F.J. ; Kastenmüller, G.

Mining the unknown: A systems approach to metabolite identification combining genetic and metabolic information.

PLoS Genet. 8:e1003005 (2012)

Theis, F.J.

Bayesian fuzzy clustering of colored graphs.

In: Theis, F.J. ; Cichocki, A.* ; Yeredor, A* ; Zibulevsky, M.* [Eds.]: Proceedings (10th international conference on Latent Variable Analysis and Signal Separation). Heidelberg: Springer, 2012. 528-535 (Lect. Notes Comput. Sc. ; 7191)

Hug, S. ; Theis, F.J.

Bayesian inference of latent causes in gene regulatory dynamics.

In: Theis, F.J. ; Cichocki, A.* ; Yeredor, A* ; Zibulevsky, M.* [Eds.]: Proceedings (10th international conference on Latent Variable Analysis and Signal Separation). Heidelberg: Springer, 2012. 520-527 (Lect. Notes Comput. Sc. ; 7191)

Illner, K. ; Fuchs, C. ; Theis, F.J.

Blind source separation using latent gaussian graphical models.

In: Larjo, A.* ; Schober, S.* ; Farhan, M.* ; Bossert, M.* ; Yli-Harja, O.* [Eds.]: Proceedings (Ninth International Workshop on Computational Systems Biology, WCSB 2012, June 4-6, 2012, Ulm, Germany). Tampere, Finnland: Tampere International Center for Signal Processing, 2012. 43-46 (Proc. WCSB ; 61)

Gutch, H.W. ; Theis, F.J.

Uniqueness of linear factorizations into independent subspaces.

J. Multivar. Anal. 112, 48-62 (2012)

Marr, C. ; Strasser, M. ; Schwarzfischer, M. ; Schroeder, T. ; Theis, F.J.

Multi-scale modeling of GMP differentiation based on single-cell genealogies.

FEBS J. 279, 3488-3500 (2012)

Petersen, A.-K. ; Krumsiek, J. ; Wägele, B. ; Theis, F.J. ; Wichmann, H.-E. ; Gieger, C. ; Suhre, K.

On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies.

BMC Bioinformatics 13:120 (2012)

Schmidl, D. ; Hug, S. ; Li, W.B. ; Greiter, M. ; Theis, F.J.

Bayesian model selection validates a biokinetic model for zirconium processing in humans.

BMC Syst. Biol. 6:95 (2012)

Buettner, F. ; Theis, F.J.

A novel approach for resolving differences in single-cell gene expression patterns from zygote to blastocyst.

Bioinformatics 28, i626-i632 (2012)

Sterz, K. ; Scherer, G. ; Krumsiek, J. ; Theis, F.J. ; Ecker, J.

Identification and quantification of 1-hydroxybutene-2-yl mercapturic acid in human urine by UPLC- HILIC-MS/MS as a novel biomarker for 1,3-butadiene exposure.

Chem. Res. Toxicol. 25, 1565-1567 (2012)

Peng, C. ; Li, N. ; Ng, Y.K. ; Zhang, J. ; Meier, F. ; Theis, F.J. ; Merkenschlager, M. ; Chen, W. ; Wurst, W. ; Prakash, N.

A unilateral negative feedback loop between miR-200 microRNAs and Sox2/E2F3 controls neural progenitor cell-cycle exit and differentiation.

J. Neurosci. 32, 13292-13308 (2012)

Krumsiek, J. ; Suhre, K. ; Illig, T. ; Adamski, J. ; Theis, F.J.

Bayesian independent component analysis recovers pathway signatures from blood metabolomics data.

J. Proteome Res. 11, 4120-4131 (2012)

Jourdan, C. ; Petersen, A.-K. ; Gieger, C. ; Döring, A. ; Illig, T. ; Wang-Sattler, R. ; Meisinger, C. ; Peters, A. ; Adamski, J. ; Prehn, C. ; Suhre, K. ; Altmaier, E. ; Kastenmüller, G. ; Römisch-Margl, W. ; Theis, F.J. ; Krumsiek, J. ; Wichmann, H.-E. ; Linseisen, J.

Body fat free mass is associated with the serum metabolite profile in a population-based study.

PLoS ONE 7:e40009 (2012)

Konrad, M. ; Vyleta, M.L. ; Theis, F.J. ; Stock, M. ; Tragust, S. ; Klatt, M. ; Drescher, V. ; Marr, C. ; Ugelvig, L.V. ; Cremer, S.

Social transfer of pathogenic fungus promotes active immunisation in ant colonies.

PLoS Biol. 10:e1001300 (2012)

Strasser, M. ; Theis, F.J. ; Marr, C.

Stability and multiattractor dynamics of a toggle switch based on a two-stage model of stochastic gene expression.

Biophys. J. 102, 19-29 (2012)

Krug, S. ; Kastenmüller, G. ; Stückler, F. ; Rist, M.J. ; Skurk, T. ; Sailer, M. ; Raffler, J. ; Römisch-Margl, W. ; Adamski, J. ; Prehn, C. ; Frank, T. ; Engel, K.-H. ; Hofmann, T. ; Luy, B. ; Zimmermann, R. ; Moritz, F. ; Schmitt-Kopplin, P. ; Krumsiek, J. ; Kremer, W. ; Huber, F. ; Oeh, U. ; Theis, F.J. ; Szymczak, W. ; Hauner, H. ; Suhre, K. ; Daniel, H.

The dynamic range of the human metabolome revealed by challenges.

FASEB J. 26, 2607-2619 (2012)

Meyer-Bäse, A. ; Cappendijk, S. ; Theis, F.J.

Uncertain gene regulatory networks simplified by gramian-based approach.

In: Arabnia, H.R.* ; Tran, Q.-N.* [Eds.]: Proceedings (2011 International Conference on Bioinformatics & Computational Biology (BIOCOMP '11), 18-21 July 2011, Las Vegas, USA). Athens, GA, USA: CSREA Press, 2012. 751-759

Lutter, D. ; Bruns, P. ; Theis, F.J.

An ensemble approach for inferring semi-quantitative regulatory dynamics for the differentiation of mouse embryonic stem cells using prior knowledge.

In: Goryanin, I.I.* ; Goryachev, A.B.* [Eds.]: Advances in Systems Biology. New York: Springer, 2012. 247-260 (Adv. Exp. Med. Biol. ; 736)

Grady, D. ; Brune, R. ; Thiemann, C. ; Theis, F.J. ; Brockmann, D.

Modularity maximization and tree clustering: Novel ways to determine effective geographic borders.

In: Thai, M.T.* ; Pardalos, P.M.* [Eds.]: Handbook of Optimization in Complex Networks. Theory and Applications. New York, NJ: Springer, 2012. 169-208 (Optimization and Its Applications ; 57)

Burtscher, I. ; Barkey, W. ; Schwarzfischer, M. ; Theis, F.J. ; Lickert, H.

The Sox17-mCherry fusion mouse line allows visualization of endoderm and vascular endothelial development.

Genesis 50, 496-505 (2012)

Vincent, E. ; Araki, S. ; Theis, F.J. ; Nolte, G. ; Bofill, P. ; Sawada, H. ; Ozerov, A. ; Gowreesunker, V. ; Lutter, D. ; Duong, N.Q.K.

The signal separation evaluation campaign (2007-2010): Achievements and remaining challenges.

Signal Process. 92, 1928-1936 (2011)

Meyer-Bäse, A. ; Plant, C. ; Krumsiek, J. ; Theis, F.J. ; Emmett, M. ; Conrad, C.A.

Stability analysis of hybrid stochastic gene regulatory networks.

In: Arabnia, H.R.* ; Tran, Q.-N.* [Eds.]: Proceedings (The 2011 International Conference on Bioinformatics and Computational Biology). Elsevier, 2011. ( ; Proceedings of BIOCOMP'11)

Lang, E.W. ; Schachtner, R. ; Lutter, D. ; Herold, D. ; Kodewitz, A. ; Blöchl, F. ; Theis, F.J. ; Keck, I.R. ; Górriz Sáez, J.M. ; Gomez, P. ; Gómez Vilda, P. ; Tomé, A.M.

Exploratory matrix factorization techniques for large scale biomedical data sets.

In: Górriz, J.M.* ; Lang, E.W.* ; Ramirez, J.* [Eds.]: Recent Advances in Biomedical Signal Processing. Sharjah: Bentham Science, 2011. 26-47

Theis, F.J. ; Kawanabe, M. ; Müller, K.-R.

Uniqueness of non-Gaussianity-based dimension reduction.

IEEE Trans. Signal Process. 59, 4478 - 4482 (2011)

Breindl, C. ; Waldherr, S. ; Wittmann, D.M. ; Theis, F.J. ; Allgoewer, F.

Steady-state robustness of qualitative gene regulation networks.

Int. J. Robust Nonlin. 21, 1742-1758 (2011)

Müller, N.S. ; Krumsiek, J. ; Theis, F.J. ; Böhm, C. ; Meyer-Bäse, A.

Gaussian graphical modeling reveals specific lipid correlations in glioblastoma cells.

Proc. SPIE 8058:805819 (2011)

Schwarzfischer, M. ; Marr, C. ; Krumsiek, J. ; Hoppe, P.S. ; Schroeder, T. ; Theis, F.J.

Efficient fluorescence image normalization for time lapse movies.

In: Proceedings (Microscopic Image Analysis with Applications in Biology, 2nd September 2011, Heidelberg, Germany). Heidelberg: MIAAB, 2011. http://www.miaab.org/miaab-2011-

Blöchl, F. ; Theis, F.J. ; Vega-Redondo, F. ; Fisher, E.

Vertex centralities in input-output networks reveal the structure of modern economies.

Phys. Rev. E 83:046127 (2011)

Krumsiek, J. ; Wittmann, D.M. ; Theis, F.J.

From discrete to continuous gene regulation models - a tutorial using the odefy toolbox.

Applications of MATLAB in Science and Engineering. Rijeka: InTech, 2011. 35-60

Kowarsch, A. ; Preusse, M. ; Marr, C. ; Theis, F.J.

miTALOS: Analyzing the tissue-specific regulation of signaling pathways by human and mouse microRNAs.

RNA 17, 809-819 (2011)

Theis, F.J. ; Latif, N. ; Wong, P. ; Frishman, D.

Complex principal component and correlation structure of 16 yeast genomic variables.

Mol. Biol. Evol. 28, 2501-2512 (2011)

Wittmann, D.M. ; Theis, F.J.

Dynamic regimes of random fuzzy logic networks.

New J. Phys. 13:013041 (2011)

Gutch, H.W. ; Krumsiek, J. ; Theis, F.J.

An ISA algorithm with unknown group sizes successfully identifies biologically meaningful clusters in metabolomics data.

In: Eur. Signal Process. Conf (19th European Signal Processing Conference, 29 August - 2 September 2011, Barcelona). Barcelona: EUSIPCO, 2011. 1733-1737

Sass, S. ; Dietmann, S. ; Burk, U.C. ; Brabletz, S. ; Lutter, D. ; Kowarsch, A. ; Mayer, K.F.X. ; Brabletz, T. ; Ruepp, A. ; Theis, F.J. ; Wang, Y.

MicroRNAs coordinately regulate protein complexes.

BMC Syst. Biol. 5:136 (2011)

Hennig, H. ; Fleischmann, R. ; Fredebohm, A. ; Hagmayer, Y. ; Nagler, J. ; Witt, A. ; Theis, F.J. ; Geisel, T.

The nature and perception of fluctuations in human musical rhythms.

PLoS ONE 6:e26457 (2011)

Krumsiek, J. ; Marr, C. ; Schroeder, T. ; Theis, F.J.

Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.

PLoS ONE 6:e22649 (2011)

Mittelstraß, K. ; Ried, J.S. ; Yu, Z. ; Krumsiek, J. ; Gieger, C. ; Prehn, C. ; Römisch-Margl, W. ; Polonikov, A. ; Peters, A. ; Theis, F.J. ; Meitinger, T. ; Kronenberg, F. ; Weidinger, S. ; Wichmann, H.-E. ; Suhre, K. ; Wang-Sattler, R. ; Adamski, J. ; Illig, T.

Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

PLoS Genet. 7:e1002215 (2011)

Laaser, I. ; Theis, F.J. ; Hrabě de Angelis, M. ; Kolb, H.-J. ; Adamski, J.

Huge splicing frequency in human Y chromosomal UTY gene.

OMICS 15, 141-154 (2011)

Krumsiek, J. ; Suhre, K. ; Illig, T. ; Adamski, J. ; Theis, F.J.

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data.

BMC Syst. Biol. 5:21 (2011)

Lang, E.W. ; Schachtner, R. ; Lutter, D. ; Herold, D. ; Kodewitz, A. ; Blöchl, F. ; Theis, F.J. ; Keck, I.R. ; Górriz Sáez, J.M. ; Gómez Vilda, P. ; Tomé, A.M.

Exploratory matrix factorization techniques for large scale biomedical data sets.

In: Górriz, J.M.* ; Lang, E.W.* ; Ramirez, J.* [Eds.]: Recent Advances in Biomedical Signal Processing. Oak Park, IL: Bentham Science Publishers, 2011. 26-47

Raia, V. ; Schilling, M. ; Böhm, M. ; Hahn, B. ; Kowarsch, A. ; Raue, A. ; Sticht, C. ; Bohl, S. ; Saile, M. ; Möller, P. ; Gretz, N. ; Timmer, J. ; Theis, F.J. ; Lehmann, W.D. ; Lichtner, P. ; Klingmüller, U.

Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-Cell lymphoma allows prediction of therapeutic targets.

Cancer Res. 71, 693-704 (2011)

Theis, F.J. ; Bohl, S. ; Klingmüller, U.

Theoretical analysis of time-to-peak responses in biological reaction networks.

Bull. Math. Biol. 73, 978-1003 (2011)

Baskaran, T. ; Blöchl, F. ; Brück, T. ; Theis, F.J.

The Heckscher-Ohlin model and the network structure of international trade.

Int. Rev. Econom. Finance 20, 135-145 (2011)

Blöchl, F. ; Wittmann, D.M. ; Theis, F.J.

Effective parameters determining the information flow in hierarchical biological systems.

Bull. Math. Biol. 73, 706-725 (2011)

Blöchl, F. ; Rascle, A. ; Kastner, J. ; Witzgall, R. ; Lang, E.W. ; Theis, F.J.

Are we to integrate previous information into microarray analyses? Interpretation of a Lmx1b-knockout experiment.

In: Górriz, J.M.* ; Lang, E.W.* ; Ramirez, J.* [Eds.]: Recent Advances in Biomedical Signal Processing. Hilversum: Bentham Science Publishers, 2011. 157-170

Theis, F.J. ; Meyer-Bäse, A.

Foundations of medical imaging and signal recording.

In: Biomedical Signal Analysis - Contemporary Methods and Applications. Cambridge, MA: MIT Press, 2010. 1-28

Meyer-Bäse, A. ; Theis, F.J. ; Emmett, M.R.

Robust stability analysis and design under consideration of multiple feedback loops of the tryptophan regulatory network of Escherichia coli.

Adv. Exp. Med. Biol. 680, 189-197 (2010)

Kowarsch, A. ; Blöchl, F. ; Bohl, S. ; Saile, M. ; Gretz, N. ; Klingmüller, U. ; Theis, F.J.

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.

BMC Bioinformatics 11:585 (2010)

Wittmann, D.M. ; Marr, C. ; Theis, F.J.

Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks.

J. Theor. Biol. 266, 436-448 (2010)

Krumsiek, J. ; Pölsterl, S. ; Wittmann, D.M. ; Theis, F.J.

Odefy - from discrete to continuous models.

BMC Bioinformatics 11, 1-10:233 (2010)

Gutch, H.W. ; Maehara, T. ; Theis, F.J.

Second order subspace analysis and simple decompositions.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 370-377 ( ; 6365)

Thiemann, C. ; Theis, F.J. ; Grady, D. ; Brune, R. ; Brockmann, D.

The structure of borders in a small world.

PLoS ONE 5:e15422 (2010)

Araki, S. ; Ozerov, A. ; Gowreesunker, V. ; Sawada, H. ; Theis, F.J. ; Nolte, G. ; Lutter, D. ; Duong, N.Q.K.

The 2010 signal separation evaluation campaign (SiSEC2010): Audio source separation.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Latent variable analysis and signal separation (Latent variable analysis and signal separation 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 114-122 (Lect. Notes Comput. Sc. ; 6365)

Araki, S. ; Theis, F.J. ; Nolte, G. ; Lutter, D. ; Ozerov, A. ; Gowreesunker, V. ; Sawada, H. ; Duong, N.Q.K.

The 2010 signal separation evaluation campaign (SiSEC2010): Biomedical source separation.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 123-130 (Lect. Notes Comput. Sc. ; 6365)

Gutch, H.W. ; Gruber, P. ; Theis, F.J.

ICA over finite fields.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 645-652 ( ; 6365)

Blöchl, F. ; Kowarsch, A. ; Theis, F.J.

Second-order source separation based on prior knowledge realized in a graph model.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 434-441 (Lect. Notes Comput. Sc. ; 6365)

Mewes, H.-W. ; Ruepp, A. ; Theis, F.J. ; Rattei, T. ; Walter, M.C. ; Frishman, D. ; Suhre, K. ; Spannagl, M. ; Mayer, K.F.X. ; Stuempflen, V. ; Antonov, A.

MIPS: Curated databases and comprehensive secondary data resources in 2010.

Nucleic Acids Res. 39, 1, D220-D224 (2010)

Theis, F.J. ; Müller, N.S. ; Plant, C. ; Böhm, C.

Robust second-order source separation identifies experimental responses in biomedical imaging.

In: Vigneron, V.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Heidelberg: Springer, 2010. 466-473 (LNCS; 6365)

Theis, F.J.

Colored subspace analysis: Dimension reduction based on a signal's autocorrelation structure.

IEEE Trans. Circuits Syst. I-Regul. Pap. 57, 1463-1474 (2010)

Hartsperger, M.L. ; Blöchl, F. ; Stuempflen, V. ; Theis, F.J.

Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs.

BMC Bioinformatics 11:522 (2010)

Kowarsch, A. ; Marr, C. ; Schmidl, D. ; Ruepp, A. ; Theis, F.J.

Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways.

PLoS ONE 5:e11154 (2010)

Blöchl, F. ; Hartsperger, M.L. ; Stuempflen, V. ; Theis, F.J.

Uncovering the structure of heterogeneus biological data: Fuzzy graph partitioning in the k-partite setting.

In: Schomburg, D.* ; Grote, A.* [Eds.]: Proceedings (German Conference on Bioinformatics 2010). Bonn: Ges. f. Inform., 2010. 31-40 ( ; P-173)

Ruepp, A. ; Kowarsch, A. ; Schmidl, D. ; Buggenthin, F. ; Brauner, B. ; Dunger, I. ; Fobo, G. ; Frishman, G. ; Montrone, C. ; Theis, F.J.

PhenomiR: A knowledgebase for microRNA expression in diseases and biological processes.

Genome Biol. 11:R6 (2010)

Konopka, W. ; Kiryk, A. ; Novak, M. ; Herwerth, M. ; Parkitna, J.R. ; Wawrzyniak, M. ; Kowarsch, A. ; Michaluk, P. ; Dzwonek, J. ; Arnsperger, T. ; Wilczynski, G. ; Merkenschlager, M. ; Theis, F.J. ; Köhr, G. ; Kaczmarek, L. ; Schütz, G.

MicroRNA loss enhances learning and memory in mice.

J. Neurosci. 30, 14835-14842 (2010)

Plant, C. ; Theis, F.J. ; Meyer-Bäse, A. ; Böhm, C.

Information-theoretic model selection for independent components.

In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 254-262 (Lect. Notes Comput. Sc. ; 6365)

Blöchl, F. ; Theis, F.J. ; Vega-Redondo, F. ; Fisher, E.O'N.

Which sectors of a modern economy are most central?

In: Empirical and theoretical methods. München: ifo Institut für Wirtschaftsforschung e.V., 2010. 1-20 (CESifo working paper series ; 3175)

Meyer-Bäse, A. ; Plant, C. ; Cappendijk, S. ; Theis, F.J.

Robust stability analysis of multi-time scale genetic regulatory networks under parametric uncertainties.

In: Proceedings (BIOCOMP'10 - The 2010 International Conference on Bioinformatics & Computational Biology). Las Vegas (Nevada): CSREA Press, 2010.

Lutter, D. ; Marr, C. ; Krumsiek, J. ; Lang, E.W. ; Theis, F.J.

Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects.

BMC Genomics 11:224 (2010)

Kreuzpointner, L. ; Simon, P. ; Theis, F.J.

The ad coefficient as a descriptive measure of the within-group agreement of ratings.

Br. J. Math. Stat. Psychol. 63, 341-360 (2010)

Theis, F.J. ; Meyer- Bäse, A.

Biomedical signal analysis: Contemporary methods and applications.

Cambridge, Mass.: MIT Press, 2010. 432 S.

Marr, C. ; Theis, F.J. ; Liebovitch, L.S. ; Hütt, M.-T.

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli.

PLoS Comput. Biol. 6, 31:e1000836 (2010)

Ansorg, M. ; Blöchl, F. ; zu Castell, W. ; Theis, F.J. ; Wittmann, D.M.

Gene regulation at the Mid-Hindbrain Boundary: Study of a mathematical model in the stationary limit.

Int. J. Biomath. Biostat. 1, 9-21 (2010)

Franke, R. ; Theis, F.J. ; Klamt, S.

From binary to multivalued to continuous models: The lac operon as a case study.

J. Integr. Bioinform. 7:151 (2010)

Blöchl, F. ; Theis, F.J.

Estimating hidden influences in metabolic and gene regulatory networks.

In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 387-394 (Lect. Notes Comput. Sc. ; 5441)

Theis, F.J. ; Cason, T.P. ; Absil, P.A.

Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold.

In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 354-361 (Lect. Notes Comput. Sc. ; 5441)

Theis, F.J. ; Neher, R. ; Zeug, A.

Blind decomposition of spectral imaging microscopy: A study on artificial and real test data.

In: Adali, T.* [Eds.]: Proceedings (Independent Component Analysis and Signal Separation). Berlin: Springer, 2009. 548-556 (Lecture Notes in Computer Science ; 5441)

Wittmann, D.M. ; Blöchl, F. ; Trümbach, D. ; Wurst, W. ; Prakash, N. ; Theis, F.J.

Spatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundary.

PLoS Comput. Biol. 5:e1000569 (2009)

Wittmann, D.M. ; Schmidl, D. ; Blöchl, F. ; Theis, F.J.

Reconstruction of graphs based on random walks.

Theor. Comput. Sci. 410, 3826-3838 (2009)

Klamt, S. ; Haus, U.-U. ; Theis, F.J.

Hypergraphs and cellular networks.

PLoS Comput. Biol. 5:e1000385 (2009)

Neher, R.A. ; Mitkovski, M. ; Kirchhoff, F. ; Neher, E. ; Theis, F.J. ; Zeug, A.

Blind source separation techniques for the decomposition of multiply labeled fluorescence images.

Biophys. J. 96, 3791-3800 (2009)

Wittmann, D.M. ; Krumsiek, J. ; Saez-Rodriguez, J. ; Lauffenburg, D.A. ; Klam, S. ; Theis, F.J.

Transforming Boolean models to continuous models: Methodology and application to T-cell receptor signaling.

BMC Syst. Biol. 3, 98:98 (2009)

Gruber, P. ; Gutch, H.W. ; Theis, F.J.

Hierarchical extraction of independent subspaces of unknown dimensions.

In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 259-266 (Lect. Notes Comput. Sc. ; 5441)

Georgiev, P.G. ; Theis, F.J.

Optimization techniques for data representions with biomedical applications.

In: Romejin, H.E.* ; Pardalos, P.M.* [Eds.]: Handbook of Optimization in Medicine. New York: Springer, 2009. 1-38 (Springer Optimization and Its Applications ; 26)

Georgiev, P.G. ; Theis, F.J.

Optimization techniques for data representations with biomedical applications.

In: Pardalos, P.M.* ; Romejin, H.E.* [Eds.]: Handbook of Optimization in Medicine. New York: Springer Science + Business Media B.V., 2009. 253-290

Webb, K.J. ; Norton, W.H.J. ; Trümbach, D. ; Meijer, A.H. ; Ninkovic, J. ; Topp, S. ; Heck, D. ; Marr, C. ; Wurst, W. ; Theis, F.J. ; Spaink, H.P. ; Bally-Cuif, L.

Zebrafish reward mutants reveal novel transcripts mediating the behavioral effects of amphetamine.

Genome Biol. 10:R81 (2009)

Gruber, P. ; Meyer-Bäse, A. ; Foo, S. ; Theis, F.J.

ICA, kernel methods and nonnegativity: New paradigms for dynamical component analysis of fMRI data.

Eng. Appl. Artif. Intel. 22, 497-504 (2009)

Brockmann, D. ; Theis, F.J.

Money Circulation, Trackable Items, and the Emergence of Universal Human Mobility Patterns.

IEEE Pervasive Comput. 7, 28-35 (2008)

Wong, P. ; Althammer, S. ; Hildebrand, A. ; Kirschner, A. ; Pagel, P. ; Geissler, B. ; Smialowski, P. ; Blöchl, F. ; Oesterheld, M. ; Schmidt, T. ; Strack, N. ; Theis, F.J. ; Ruepp, A. ; Frishman, D.

An evolutionary and structural characterization of mammalian protein complex organization.

BMC Genomics 9:629 (2008)

Begemann, M. ; Sargin, D. ; Rossner, M.J. ; Bartels, C. ; Theis, F.J. ; Wichert, S.P. ; Stender, N. ; Fischer, B. ; Sperling, S. ; Stawicki, S. ; Wiedl, A. ; Falkai, P. ; Nave, K.A. ; Ehrenreich, H.

Episode-specific differential gene expression of peripheral blood mononuclear cells in rapid cycling supports novel treatment approaches.

Mol. Med. 14, 546-552 (2008)

Adamcio, B. ; Sargin, D. ; Stradomska, A. ; Medrihan, L. ; Gertler, C. ; Theis, F.J. ; Zhang, M. ; Müller, M. ; Hassouna, I. ; Hannke, K. ; Sperling, S. ; Radyushkin, K. ; El-Kordi, A. ; Schulze, L. ; Ronnenberg, A. ; Wolf, F. ; Brose, N. ; Rhee, J.S. ; Zhang, W. ; Ehrenreich, H.

Erythropoietin enhances hippocampal long-term potentiation and memory.

BMC Biol. 6:37 (2008)

Lutter, D. ; Ugocsai, P. ; Grandl, M. ; Orso, E. ; Theis, F.J. ; Lang, E.W. ; Schmitz, G.

Analyzing M-CSF dependent monocyte/macrophage differentiation: expression modes and meta-modes derived from an independent component analysis.

BMC Bioinformatics 9:100 (2008)

Theis, F.J. ; Gruber, P. ; Keck, I.R. ; Lang, E.W.

A robust model for spatiotemporal dependencies.

Neurocomp. 71, 2209-2216 (2008)

Schachtner, R. ; Lutter, D. ; Knollmüller, P. ; Tomé, A.M. ; Theis, F.J. ; Schmitz, G. ; Stetter, M. ; Vilda, P.G. ; Lang, E.W.

Knowledge-based gene expression classification via matrix factorization.

Bioinformatics 24, 1688-1697 (2008)

Gutch, H.W. ; Theis, F.J.