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FunCat functional inference with belief propagation and feature integration

Paper ID Volume ID Publish Year Pages File Format Full-Text
15481 1416 2008 3 PDF Available
Title
FunCat functional inference with belief propagation and feature integration
Abstract

Pairwise comparison of sequence data is intensively used for automated functional protein annotation, while graphical models emerge as promising candidates for an integration of various heterogeneous features. We designed a model, termed hRMN that integrates different genomic features and implemented a variant of belief propagation for functional annotation transfer. hRMN allows the assignment of multiple functional categories while avoiding common problems in annotation transfer from heterogeneous datasets, such as an independency of the investigated datasets. We benchmarked this system with large-scale annotation transfer (based on the MIPS FunCat ontology) to proteins of the prokaryotes Bacillus subtilis, Helicobacter pylori, Listeria monocytogenes, and Listeria innocua. hRMN consistently outperformed two competitors in annotation of four bacterial genomes. The developed code is available for download at http://mips.gsf.de/proj/bfab/hRMN.html.

Keywords
Automatic functional annotation; Belief propagation; Bacterial genomes; Heterogeneous data sources; Probabilistic graphical models
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 32, Issue 5, October 2008, Pages 375–377
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us