computational
modeling in biology

Schriftgröße »A . A+ . A++ .

Daniel Schmidl

PhD student


Tel.: +49 (0) 89 3187 2876
Room: 155


Research

  • Bayesian model selection for highly indeterminate systems
  • Bayesian parameter inference in biological systems
  • Vine copula decomposition
  • Statistical analysis of genetic effects on metabolite ratios
  • MicroRNAs in human diseases

 

Publications

  • Ruepp A, Kowarsch A, Schmidl D, Buggenthin F, Brauner B, Dunger I, Fobo G, Frishman G, Montrone C, and Theis FJ. PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes. Genome Biology 11(1):R6, 2010
  • Kowarsch A, Marr Carsten, Schmidl D, Ruepp A, and Theis FJ. Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways. PLoS one 5(6), 2010
  • Wittmann DM, Schmidl D, Blöchl F, and Theis FJ. Reconstruction of graphs based on random walks. J Theor Comput Sci 410, 2009

 

Conference contributions

  • Schmidl D, Czado C, and Theis FJ. Copula based Markov Chain Monte Carlo methods improve effective sampling times for parameter inference in highly dependent dynamic models. 4th Workshop on Vine Copula Distributions and Applications 2011, Garching
  • Schmidl D, Wittmann DM, Bohl S, Klingmüller U, and Theis FJ. A Markov Chain Monte Carlo approach identifies reaction rates and model uncertainties in the JAK-STAT pathway. Conference on Systems Biology of Human Disease 2010, Boston
  • Kowarsch A, Schmidl D, Marr C, Ruepp A, and Theis FJ. MicroRNA-affected signaling pathways in human diseases. Workshop on Data to Dynamics 2009, Freising
  • Schmidl D, Wittmann DM, Bohl S, Klingmüller U, and Theis FJ. Identifying kinetic constants and parameter indeterminacies in dynamic biological systems using MCMC sampling. Workshop on Statistical Methods for Dynamical System Models 2009, Vancouver
  • Schmidl D, Wittmann DM, Blöchl F, and Theis FJ. Reconstructing graphs from random walk distances. Spring School 2008 on Systems Biology, Kloster Seeon

 

 Curriculum Vitae

Daniel Schmidl studied Mathematics with minor subjects Computer Science and Physics at the University of Regensburg. During his studies he focused on Algebraic Geometry, Differential Geometry and Linear Programming, combining some of these fields in his diploma thesis on the "System of Differential Equations of Kloosterman's type". He graduated in 2007 and is currently working as a PhD student at the Statistics department of the Technische University Munich, as well as at the Institute of Bioinformatics, located at the Helmholtz Research Center Munich.