KmalPred: a deep learning framework for lysine malonylation site prediction using protein language model representations.

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Bibliographic Details
Title: KmalPred: a deep learning framework for lysine malonylation site prediction using protein language model representations.
Authors: Jiao S; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China., Ao C; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China., Zou Q; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China., Yang H; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China. huanyang@csj.uestc.edu.cn.
Source: BMC biology [BMC Biol] 2026 May 19; Vol. 24 (1). Date of Electronic Publication: 2026 May 19.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101190720 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-7007 (Electronic) Linking ISSN: 17417007 NLM ISO Abbreviation: BMC Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1741-7007
DOI:10.1186/s12915-026-02636-1