ArticleBioinformatics (Oxford, England)2022
Inverse Potts model improves accuracy of phylogenetic profiling.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- CORGIAS: identifying correlated gene pairs by considering evolutionary history in a large-scale prokaryotic genome dataset.NAR genomics and bioinformatics · 2025Article
- ParallelEvolCCM: Quantifying Coevolutionary Patterns Among Genomic Features.Genome biology and evolution · 2025Article
- EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.Nature communications · 2025Article
- Phylogenetic Profiling Analysis of the Phycobilisome Revealed a Novel State-Transition Regulator Gene in Synechocystis sp. PCC 6803.Plant & cell physiology · 2024Article
- Frequent nonhomologous replacement of replicative helicase loaders by viruses inProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Mirage 2.0: fast and memory-efficient reconstruction of gene-content evolution considering heterogeneous evolutionary patterns among gene families.Bioinformatics (Oxford, England) · 2022Article
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2 authors.
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Abstract
motivationPhylogenetic 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.
resultsTo 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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