Literature DB >> 17990508

Assessing and combining reliability of protein interaction sources.

Sonia Leach1, Aaron Gabow, Lawrence Hunter, Debra S Goldberg.   

Abstract

Integrating diverse sources of interaction information to create protein networks requires strategies sensitive to differences in accuracy and coverage of each source. Previous integration approaches calculate reliabilities of protein interaction information sources based on congruity to a designated 'gold standard.' In this paper, we provide a comparison of the two most popular existing approaches and propose a novel alternative for assessing reliabilities which does not require a gold standard. We identify a new method for combining the resultant reliabilities and compare it against an existing method. Further, we propose an extrinsic approach to evaluation of reliability estimates, considering their influence on the downstream tasks of inferring protein function and learning regulatory networks from expression data. Results using this evaluation method show 1) our method for reliability estimation is an attractive alternative to those requiring a gold standard and 2) the new method for combining reliabilities is less sensitive to noise in reliability assignments than the similar existing technique.

Mesh:

Year:  2007        PMID: 17990508      PMCID: PMC2517251     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  30 in total

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2.  BIND--The Biomolecular Interaction Network Database.

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4.  Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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5.  Inferring subnetworks from perturbed expression profiles.

Authors:  D Pe'er; A Regev; G Elidan; N Friedman
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6.  Predictome: a database of putative functional links between proteins.

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9.  MIPS: a database for genomes and protein sequences.

Authors:  H W Mewes; D Frishman; U Güldener; G Mannhaupt; K Mayer; M Mokrejs; B Morgenstern; M Münsterkötter; S Rudd; B Weil
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10.  A network of protein-protein interactions in yeast.

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  4 in total

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Journal:  PLoS Comput Biol       Date:  2009-03-27       Impact factor: 4.475

3.  Predicting protein linkages in bacteria: which method is best depends on task.

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4.  OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.

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  4 in total

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