Computational systems biology aims at the data-based estimation of models as abstractions of biological processes. The models are then used to guide further experimentation. Data-based modeling searches both for model structures as well as dynamic parameters to explain and fit observed data as well as possible. A central issue in the biological field lies in the typically low number of observed species and time points. The resuling estimation problems are thus often ill-posed, and we have to account for model indeterminacies. Instead of following the standard least-squares or maximum-likelihood approach, we therefore aim at inferring parameter distributions instead of only searching for the best fit. We do this in a Bayesian framework using Markov-Chain Monte-Carlo sampling.
In the talk, I will introduce the estimation problem and visualize this on a few examples from molecular biology, both on deterministic and stochastic dynamical systems. Then I will show how we adapted estimation techniques to account for the problems in molecular biology. Applications will be model inference and selection to describe cellular decisions.
Fabian Theis obtained MSc degrees in Mathematics and Physics at the University of Regensburg in 2000. He also received a PhD degree in Physics from the same university in 2002 and a PhD in Computer Science from the University of Granada in 2003. He worked as visiting researcher at the department of Architecture and Computer Technology (University of Granada, Spain), at the RIKEN Brain Science Institute (Wako, Japan), at FAMU-FSU (Florida State University, USA) and at TUAT's Laboratory for Signal and Image Processing (Tokyo, Japan), and headed the 'signal processing & information theory' group at the Institute of Biophysics (Regensburg, Germany). In 2006, he started working as Bernstein fellow leading a junior research group at the Bernstein Center for Computational Neuroscience, located at the Max Planck Institute for Dynamics and Self-Organisation at Göttingen. In summer 2007, Fabian Theis became working group head of CMB at the Institute of Bioinformatics at the Helmholtz Center Munich. In spring 2009, he became associate Professor for Mathematics in Systems Biology at the Math Department of the TU Munich. Since 2009 he is member of the "Young Academy" (founded by the Berlin-Brandenburg Academy of Sciences and Humanities and the German Academy of Natural Scientists Leopoldina). In 2010 he was awarded an ERC starting grant. His research interests include gene regulation and dynamical modeling, biostatistics and network analyses, statistical signal processing and biomedical data analysis.
Go to Top