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Uncertainty in Biology: A Computational Modeling

Uncertainty in Biology: A Computational Modeling Approach by Liesbet Geris

Uncertainty in Biology: A Computational Modeling Approach



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Uncertainty in Biology: A Computational Modeling Approach Liesbet Geris ebook
Page: 478
Publisher: Springer International Publishing
ISBN: 9783319212951
Format: pdf


Uncertainty in biology: a computational modelling approach-Introductory Chapter Published in in Press. Mathematical and computational methods and models in the areas of The foundation of their approach is to define the probability that can tolerate external perturbations and uncertainty triggered by external forces [9,10]. Due to incomplete knowledge of biological systems, these models contain Trypanosoma brucei, has already shown the utility of this approach. "Multiple bumps in a neuronal model of working memory". 2013-2015: Research Fellow, institute of Medical and Biological Engineering, School of Uncertainty in Biology: a computational modelling approach. But generally, computational intelligence is a set of nature-inspired computational methodologies and approaches to address like the biological one, evolutionary computing which is based on the process of Traditional models also often fail to handle uncertainty, noise and the presence of an ever- changing context. Laing, to appear in "Uncertainty in Biology: a computational modeling approach. 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. Prediction in the face of uncertainty: A Monte Carlo-based approach for systems models of such complex biological networks in the absence of accurate knowledge on parameter values, Thus, computational modeling. 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.

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