Author

Liang Gao

Chinese Academy of SciencesORCID 0009-0001-3883-0945Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Liang Gao2 papers · University of California, Los Angeles

Biology Disciplines

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Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:phylogenetics / evolution· 1 Approach:statistical model· 1

Frequent Co-Authors

Stefan GrünewaldiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

1 paper

Recent·Most cited

Evolutionary BiologybioRxivPreprintJul 10, 2025

A Maximum-Likelihood Method to Construct Phylogenetic Trees Using Low-Homoplasy Markers: New Insights into Neoaves Phylogeny

Liang Gao, Stefan Grünewald

This paper introduces MLRE, a maximum-likelihood method for species tree reconstruction using low-homoplasy markers, showing improved performance on simulated data and better agreement with published Neoaves phylogenies.

DOI 10.1101/2025.07.10.664098

deep learningstatistical model

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