Systems biology: parameter estimation for biochemical models

By M. Ashyraliyev, Y. Fomekong-Nanfack, J. Kaandorp, Joke G. Blom. The FEBS Journal, 2009

365 citations recorded by the source corpus.

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Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems (2016, background): “…a mechanistic explanation when correct, these equations have a known challenge that they are often of preset form and have sensitive parameters (Apgar et al., 2010; Ashyraliyev et al., 2009; Gutenkunst et al., 2007), such that achieving accurate predictions within one dataset risks overfitting.”
Inference of complex biological networks: distinguishability issues and optimization-based solutions (2011, background): “However, and despite a number of works illustrating ways to test the structural and practical identifiability of models [65-67], a significant portion of modeling studies in systems biology continue to ignore this key property.”
Dynamical analysis of a prey–predator model with Beddington–DeAngelis type function response incorporating a prey refuge (2014, methodology): “The parameter estimation [41,42] can be done using one of the many well-established algorithms such as trial-and-error processes, numerical optimization techniques such as conjugate gradient method, trust region methods and genetic algorithms (see [43–45]).”
Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy (2017, methodology): “Due to the non-convexity of the parameter estimation problem above, suitable global optimization must be used [31, 33, 35, 52–54].”