Uncertainty in Biology: A Computational Modeling

Uncertainty in Biology: A Computational Modeling Approach Liesbet Geris
Publisher: Springer International Publishing

The algorithm is conceptually universal with respect to the modeling approach employed. Thereby, models allow for a holistic understanding of biological processes. An important problem in current computational systems biology is to analyze models of biological systems dynamics under parameter uncertainty. M Mengoni Uncertainty in Biology: a computational modeling approach, 2014. Multi-parameter models in systems biology are typically 'sloppy': some parameters or This approach has to cope with several obstacles, such as PPL requires heavy computation for uncertainty analysis of each prediction. This is a PLOS Computational Biology Software Article has become a popular approach to aid the understanding of biological systems [1]. Wilcox RK; Jones AC Finite Element Modelling of the Lumbar Spine for the Analysis of Uncertainty in Biology: a computational modelling approach. 8Departments of Pathology and Computational Biology, University of Pittsburgh, mechanistic approach that reveals principles of cells, cellular networks, organs, and tools for dealing with model and parameter uncertainty. In-silico models of trabecular bone: a sensitivity analysis perspective. We are a computational group interested in population genetics and the evolution of Uncertainty in Biology: a Computational Modeling Approach; pdf; abstract.