Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
SIAM Journal on Optimization
Globalized Nelder-Mead method for engineering optimization
ICECT'03 Proceedings of the third international conference on Engineering computational technology
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
Real-time prediction in a stochastic domain via similarity-based data-mining
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Focus on discovering mechanisms: a relativistic, agent-directed, perfused liver
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Parameter Estimation Using Metaheuristics in Systems Biology: A Comprehensive Review
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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We present a method for estimating (predicting) parameter values for an agent-based model of in silico hepatocytes (ISH). The method enables the ISH to interact with simulated drugs to reasonably match results from in vitro hepatocyte excretion studies. Further, we make the estimation method available to the model, itself, to enable it to reasonably anticipate (predict) the biliary transport and excretion properties of a new compound based on the acceptable parameter values for previously encountered compounds. We use Fuzzy c-Means (FCM) classification algorithm to determine the degree of similarity between previously tuned compounds and the new compound. Specifically, a set of simulation parameters for enkephalin was predicted using the tuned parameter values of salicylate, taurocholate, and methotrexate. The feature space for the FCM classification is the physicochemical properties of the compounds.