title: Linking genome-scale metabolic modeling and genome annotation.
abstract: Genome-scale metabolic network reconstructions, assembled from annotated genomes, serve as a platform for integrating data from heterogeneous sources and generating hypotheses for further experimental validation. Implementing constraint-based modeling techniques such as flux balance analysis (FBA) on network reconstructions allows for interrogating metabolism at a systems level, which aids in identifying and rectifying gaps in knowledge. With genome sequences for various organisms from prokaryotes to eukaryotes becoming increasingly available, a significant bottleneck lies in the structural and functional annotation of these sequences. Using topologically based and biologically inspired metabolic network refinement, we can better characterize enzymatic functions present in an organism and link annotation of these functions to candidate transcripts; both steps can be experimentally validated.
authors: Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
authors: Edik M
authors: EM
authors: Blais
authors: Arvind K
authors: AK
authors: Chavali
authors: Jason A
authors: JA
authors: Papin
mesh_terms: D019295:Computational Biology; D030541:Databases, Genetic; D016678:Genome; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic; D058977:Molecular Sequence Annotation / Q000379:methods*; D016366:Open Reading Frames; D017422:Sequence Analysis, DNA; D012984:Software