ArticleMolecular biology and evolution2024
Discovering Fragile Clades and Causal Sequences in Phylogenomics by Evolutionary Sparse Learning.
Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Phylogenomic subsampling and upsampling for efficient evolutionary analyses of big data.Molecular biology and evolution · 2026Article
- Phylogenomic subsampling and upsampling for efficient evolutionary analyses of big data.bioRxiv : the preprint server for biology · 2026Article
- MEGA 12.1: Cross-Platform Release for macOS and Linux Operating Systems.Journal of molecular evolution · 2026Article
- A Multidrug and Toxic Compound Extrusion Transporter, RgMATE6, Facilitates Vacuolar Transport of Acteoside inPlants (Basel, Switzerland) · 2025Article
- MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.Molecular biology and evolution · 2025Article
- Article
- MEGA-GPT: Artificial Intelligence Guidance and Building Analytical Protocols Using MEGA Software.Molecular biology and evolution · 2025Article
- Identification of antagonistic activity againstFrontiers in microbiology · 2025Article
- MEGA12: Molecular Evolutionary Genetic Analysis Version 12 for Adaptive and Green Computing.Molecular biology and evolution · 2024Article
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2 authors.
Funding
Abstract
Phylogenomic analyses of long sequences, consisting of many genes and genomic segments, reconstruct organismal relationships with high statistical confidence. But, inferred relationships can be sensitive to excluding just a few sequences. Currently, there is no direct way to identify fragile relationships and the associated individual gene sequences in species. Here, we introduce novel metrics for gene-species sequence concordance and clade probability derived from evolutionary sparse learning models. We validated these metrics using fungi, plant, and animal phylogenomic datasets, highlighting the ability of the new metrics to pinpoint fragile clades and the sequences responsible. The new approach does not necessitate the investigation of alternative phylogenetic hypotheses, substitution models, or repeated data subset analyses. Our methodology offers a streamlined approach to evaluating major inferred clades and identifying sequences that may distort reconstructed phylogenies using large datasets.
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Registered trials
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