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• W2172574008 abstract "Abstract Summary: 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." @default.
• W2172574008 created "2016-06-24" @default.
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• W2172574008 date "2015-11-26" @default.
• W2172574008 modified "2023-10-05" @default.
• W2172574008 title "SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles" @default.
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• W2172574008 doi "https://doi.org/10.1093/bioinformatics/btv696" @default.
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