Predicting phenotype from genotype through automatically composed petri nets

  • Authors:
  • Mary Ann Blätke;Monika Heiner;Wolfgang Marwan

  • Affiliations:
  • Magdeburg Centre for Systems Biology and Lehrstuhl für Regulationsbiologie, Otto-von-Guericke-Universität, Magdeburg, Germany;Chair of Data Structures and Software Dependability, Brandenburg Technical University, Cottbus, Germany;Magdeburg Centre for Systems Biology and Lehrstuhl für Regulationsbiologie, Otto-von-Guericke-Universität, Magdeburg, Germany

  • Venue:
  • CMSB'12 Proceedings of the 10th international conference on Computational Methods in Systems Biology
  • Year:
  • 2012

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Abstract

We describe a modular modelling approach permitting curation, updating, and distributed development of modules through joined community effort overcoming the problem of keeping a combinatorially exploding number of monolithic models up to date. For this purpose, the effects of genes and their mutated alleles on downstream components are modeled by composable, metadata-containing Petri net models organized in a database with version control, accessible through a web interface (www.biomodelkit.org). Gene modules can be coupled to protein modules through mRNA modules by specific interfaces designed for the automatic, database-assisted composition. Automatically assembled executable models may then consider cell type-specific gene expression patterns and the resulting protein concentrations. Gene modules and allelic interference modules may represent effects of gene mutation and predict their pleiotropic consequences or uncover complex genotype/phenotype relationships. Forward and reverse engineered modules are fully compatible.