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Predicting Phenotype from Genotype through Automatically Composed Petri Nets

  • Mary Ann Blätke
  • Monika Heiner
  • Wolfgang Marwan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7605)

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.

Keywords

Biomodel engineering formal language data integration high-throughput quantitative trait loci 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mary Ann Blätke
    • 1
  • Monika Heiner
    • 2
  • Wolfgang Marwan
    • 1
  1. 1.Magdeburg Centre for Systems Biology and Lehrstuhl für RegulationsbiologieOtto-von-Guericke-UniversitätMagdeburgGermany
  2. 2.Chair of Data Structures and Software DependabilityBrandenburg Technical UniversityCottbusGermany

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