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SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles


Franceschini, Andrea; Lin, Jianyi; von Mering, Christian; Jensen, Lars Juhl (2016). SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles. Bioinformatics, 32(7):1085-1087.

Abstract

A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods.
AVAILABILITY AND IMPLEMENTATION: The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy CONTACT: lars.juhl.jensen@cpr.ku.dk
Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract

A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods.
AVAILABILITY AND IMPLEMENTATION: The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy CONTACT: lars.juhl.jensen@cpr.ku.dk
Supplementary information: Supplementary data are available at Bioinformatics online.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
08 University Research Priority Programs > Systems Biology / Functional Genomics
08 University Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2016
Deposited On:04 Feb 2016 10:11
Last Modified:21 Nov 2017 18:19
Publisher:Oxford University Press
ISSN:1367-4803
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btv696
PubMed ID:26614125

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