{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T08:09:56Z","timestamp":1779178196521,"version":"3.51.4"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T00:00:00Z","timestamp":1779148800000},"content-version":"vor","delay-in-days":18,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373080"],"award-info":[{"award-number":["62373080"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62450002"],"award-info":[{"award-number":["62450002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372332"],"award-info":[{"award-number":["62372332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62531002"],"award-info":[{"award-number":["62531002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sichuan Tianfu Emei Plan"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Liquid\u2013liquid phase separation (LLPS) is a key mechanism driving the assembly of membrane-less organelles and is increasingly recognized for its involvement in essential cellular functions and various diseases. However, existing computational approaches largely rely on sequence-level descriptors and often fail to explicitly incorporate structural topology information, limiting their ability to capture the complex determinants of LLPS behavior. Accurate identification of LLPS-capable proteins remains challenging due to their sequence diversity and complex structural determinants. Here, we present MuFGPS (Multi-level Feature Graph-based Predictor for Phase-Separating proteins), a predictive framework integrating sequence-derived physicochemical features, Define Secondary Structure of Proteins-annotated secondary structures, and graph-based structural embeddings from AlphaFold residue contact maps via a multi-head Graph Attention Network. Class imbalance is addressed using Synthetic Minority Oversampling Technique (SMOTE), and classification is performed through a stacking ensemble of Random Forest, XGBoost, and LightGBM. Benchmarks against six representative methods demonstrate that MuFGPS achieves superior performance across all metrics, with notable gains in F1-score and matthews correlation coefficient (MCC). Ablation analyses confirm the synergistic contributions of structural features and ensemble learning to accuracy and robustness. MuFGPS offers a scalable and high-accuracy framework for proteome-wide LLPS protein prediction.<\/jats:p>","DOI":"10.1093\/bib\/bbag235","type":"journal-article","created":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T11:44:08Z","timestamp":1777031048000},"source":"Crossref","is-referenced-by-count":0,"title":["MuFGPS: enhancing liquid\u2013liquid phase separation protein prediction through multi-level features and ensemble learning"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-8569-8023","authenticated-orcid":false,"given":"Lei","family":"Xian","sequence":"first","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, Sichuan ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-1142","authenticated-orcid":false,"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, Sichuan ,","place":["China"]},{"name":"Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Science, Macao Polytechnic University , R. de Lu\u00eds Gonzaga Gomes, Macau 999078 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ren","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology , No. 5, Zhongguancun South Street, Haidian District, Beijing 100081 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