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Parameter discovery for stochastic computational models in systems biology using Bayesian model checking
2014
2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)
Parameterized probabilistic complex computational (P 2 C 2 ) models are being increasingly used in computational systems biology for analyzing biological systems. A key challenge is to build mechanistic P 2 C 2 models by combining prior knowledge and empirical data, given that certain system properties are unknown. These unknown components are incorporated into a model as parameters and determining their values has traditionally been a process of trial and error. We present a new algorithmic
doi:10.1109/iccabs.2014.6863925
dblp:conf/iccabs/HussainLMDVJ14
fatcat:klj3qtidwnbfxaekrlllzdk7iq