MP-GeneticSynth: inferring biological network regulations from time series
Alberto Castellini1, Daniele Paltrinieri2, Vincenzo Manca3
1Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy Center for BioMedical Computing, Verona University, 37134 Verona, Italy, Max Planck Institute for Molecular Plant Physiology-Syst Bio & Math Modelling Group, 14476, Germany, University of Potsdam, Institute for Biochemistry and Biology - Bioinformatics Group, 14476, Germany and Department of Computer Science, Verona University, 37134 Verona, Italy.
Abstract:
MP-GeneticSynth is a Java tool for discovering the logic and regulation mechanisms responsible for observed biological dynamics in terms of finite difference recurrent equations. The software makes use of: (i) metabolic P systems as a modeling framework, (ii) an evolutionary approach to discover flux regulation functions as linear combinations of given primitive functions, (iii) a suitable reformulation of the least squares method to estimate function parameters considering simultaneously all the reactions involved in complex dynamics. The tool is available as a plugin for the virtual laboratory MetaPlab. It has graphical and interactive interfaces for data preparation, a priori knowledge integration, and flux regulator analysis. Availability and implementation: Source code, binaries, documentation (including quick start guide and videos) and case studies are freely available at http://mplab.sci.univr.it/plugins/mpgs/index.html.
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