Uncertainty in Biology A Computational Modeling Approach /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Geris, Liesbet (Επιμελητής έκδοσης), Gomez-Cabrero, David (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Έκδοση: 1st ed. 2016.
• Σειρά: Studies in Mechanobiology, Tissue Engineering and Biomaterials, 17
• Θέματα: Engineering.; Bioinformatics.; Computational biology.; Computer mathematics.; Biomedical engineering.; Biomedical Engineering.; Computational Science and Engineering.; Computer Appl. in Life Sciences.

Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies.  Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obt...

Πίνακας περιεχομένων:

• An Introduction to Uncertainty in the Development of Computational Models of Biological Processes
• Reverse Engineering under Uncertainty
• Probabilistic Computational Causal Discovery for Systems Biology
• Macroscopic Simulation of Individual-Based Stochastic Models for Biological Processes
• The Experimental Side of Parameter Estimation
• Statistical Data Analysis and Modeling
• Optimization in Biology: Parameter Estimation and the Associated Optimization Problem
• Interval Methods
• Model Extension and Model Selection
• Bayesian Model Selection Methods and their Application to Biological ODE Systems
• Sloppiness and the Geometry of Parameter Space
• Modeling and Model Simplification to Facilitate Biological Insights and Predictions
• Sensitivity Analysis by Design of Experiments
• Waves in Spatially-Disordered Neural Fields: a Case Study in Uncertainty Quantification
• X In-silico Models of Trabecular Bone: a Sensitivity Analysis Perspective
• Neuroswarm: a Methodology to Explore the Constraints that Function Imposes on Simulation Parameters in Large-Scale Networks of Biological Neurons
• Prediction Uncertainty Estimation Despite Unidentifiability: an Overview of Recent Developments
• Computational Modeling Under Uncertainty: Challenges and Opportunities.