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Cited by 8Genomics and Phylogenetic StudiesBioinformatics and Genomic NetworksMachine Learning in Bioinformatics

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Inverse Potts model improves accuracy of phylogenetic profiling

Open access
Fukunaga, Tsukasa, Iwasaki, Wataru·2022·Bioinformatics
DOI 10.1093/bioinformatics/btac034PMC PMC8963296

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Abstract

Motivation: Phylogenetic profiling is a powerful computational method for revealing the functions of function-unknown genes. Although conventional similarity metrics in phylogenetic profiling achieved high prediction accuracy, they have two estimation biases: an evolutionary bias and a spurious correlation bias. While previous studies reduced the evolutionary bias by considering a phylogenetic tree, few studies have analyzed the spurious correlation bias. Results: To reduce the spurious correlation bias, we developed metrics based on the inverse Potts model (IPM) for phylogenetic profiling. We also developed a metric based on both the IPM and a phylogenetic tree. In an empirical dataset analysis, we demonstrated that these IPM-based metrics improved the prediction performance of phylogenetic profiling. In addition, we found that the integration of several metrics, including the IPM-based metrics, had superior performance to a single metric. Availability and implementation: The source code is freely available at https://github.com/fukunagatsu/Ipm. Supplementary information: Supplementary data are available at Bioinformatics online.

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Metadata

Authors
Fukunaga, T., & Iwasaki, W.
Affiliations
  • Waseda University (JP)
  • Institute for Quantitative Biosciences, The University of Tokyo (JP)
Corresponding author
Fukunaga, Tsukasa
ORCID
Venue
Bioinformatics
Publisher
Oxford University Press (OUP)
Published
2022-01-21
Volume
38
Issue
7
Pages
1794-1800
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
DOI
10.1093/bioinformatics/btac034
PMC
PMC8963296
OpenAlex
W4205933632
Cited by
8
References
5
Citations by year
2025: 3 · 2024: 3 · 2022: 2
FWCI
0.65
Type
journal article
Language
en
Open access
Licence
Locations
  • Bioinformatics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
Japan Society for the Promotion of Science (JP19K20395, JP20H05582, 16H06279, 19H05688)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Keywords
phylogenetic profiling, gene function prediction, phylogenetic tree, similarity measures
MeSH terms
Phylogeny, Software

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