ProMoHGT: a heterogeneous graph transformer with graph contrastive learning for robust microbial protein function prediction

Abstract Proteins serve as the central executors of life activities, performing diverse functions such as metabolic catalysis, genetic regulation, signal transduction, and cytoskeletal maintenance. However, microbial proteins face unique challenges: their rapid evolution leads to low sequence conser...

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Hauptverfasser:	Jianan Sui, Xiaomiao Wang, Yufeng Su, Menglong Gao, Huanjie Huang, Hao Liu, Jianfeng Zhang, Yaohan Tang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	BMC 2025-12-01
Schriftenreihe:	BMC Genomics
Schlagworte:	Microbial protein annotation Heterogeneous graph transformer Graph contrastive learning Multi-source feature integration
Online-Zugang:	https://doi.org/10.1186/s12864-025-12383-2
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