期刊
BIOINFORMATICS
卷 32, 期 7, 页码 1085-1087出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv696
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资金
- Swiss Institute of Bioinformatics
- Novo Nordisk Foundation [NNF14CC0001]
- Novo Nordisk Foundation Center for Protein Research [PI Lars Juhl Jensen] Funding Source: researchfish
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.
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