{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T08:36:06Z","timestamp":1776760566423,"version":"3.51.2"},"reference-count":22,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:p>This study addresses the problem of protein function annotation and proposes a multi-source biological information-fusion framework called Functional co-Occurrence Probability Estimation (FOPE) for estimating functional co-occurrence probabilities. The framework integrates Protein\u2013Protein Interaction (PPI) network topology and protein domain information, quantifying the functional synergy between protein pairs through bidirectional functional participation modeling. Experiments on four model organisms (A. thaliana, C. elegans, D. melanogaster, and S. cerevisiae) show that FOPE delivers effective predictions for the three main categories of Gene Ontology (GO). Compared to existing representative methods, its macro-Fmax values improved by 25.3%, 19.3%, and 20.9% on average for Biological Process (BP), Cellular Component (CC), and Molecular Function (MF), respectively. Ablation studies further reveal the functional-specific contributions of different information sources: domain information plays a dominant role in MF prediction, while PPI network features are more critical for BP prediction. The effective integration of both is key to achieving comprehensive prediction performance. Robustness tests demonstrate that FOPE maintains strong stability in BP and CC predictions even under significant noise in the PPI network (adding or removing 30% of interactions), verifying the error-tolerance advantages of multi-source information fusion. The FOPE framework proposed in this study provides a feasible information fusion approach for protein function prediction. Preliminary experimental results demonstrate the applicability of the method across different functional categories and multiple model organisms, offering a potential computational pathway for exploring functional synergy relationships among proteins from a system-level perspective.<\/jats:p>","DOI":"10.1142\/s0219720026500046","type":"journal-article","created":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T09:38:46Z","timestamp":1773999526000},"source":"Crossref","is-referenced-by-count":0,"title":["Predicting functional co-occurrence probability in PPI networks via multi-level participation expectation"],"prefix":"10.1142","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8726-3214","authenticated-orcid":false,"given":"Peng","family":"Wang","sequence":"first","affiliation":[{"name":"Chongqing Key Laboratory of Intelligent Perception and Blockchain Technology, School of Artificial Intelligence, Chongqing Technology and Business University, Chongqing 400067, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2026,4,21]]},"reference":[{"key":"S0219720026500046BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2019.12.004"},{"key":"S0219720026500046BIB002","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkae1010"},{"key":"S0219720026500046BIB003","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkae1082"},{"key":"S0219720026500046BIB004","doi-asserted-by":"publisher","DOI":"10.1093\/genetics\/iyad031"},{"key":"S0219720026500046BIB005","doi-asserted-by":"publisher","DOI":"10.1038\/nrg.2017.38"},{"key":"S0219720026500046BIB006","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0076339"},{"key":"S0219720026500046BIB007","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaa913"},{"key":"S0219720026500046BIB008","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-3460-7"},{"issue":"1","key":"S0219720026500046BIB009","first-page":"395","volume":"7","author":"Liang S.","year":"2009","journal-title":"BMC Syst. Biol."},{"key":"S0219720026500046BIB010","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-395"},{"key":"S0219720026500046BIB011","doi-asserted-by":"publisher","DOI":"10.1186\/1752-0509-8-35"},{"key":"S0219720026500046BIB012","doi-asserted-by":"crossref","unstructured":"W. Peng, M. Li, L. Chen and L. Wang, Predicting protein functions by using unbalanced random walk algorithm on three biological networks,\n                      14\n                      (2):360\u2013369, 2017, http:\/\/ieeexplore.ieee.org\/document\/7015578\/.","DOI":"10.1109\/TCBB.2015.2394314"},{"key":"S0219720026500046BIB013","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03663-7"},{"key":"S0219720026500046BIB014","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl145"},{"key":"S0219720026500046BIB015","doi-asserted-by":"publisher","DOI":"10.1093\/genetics\/iyad211"},{"key":"S0219720026500046BIB016","doi-asserted-by":"publisher","DOI":"10.1093\/genetics\/iyae050"},{"key":"S0219720026500046BIB017","doi-asserted-by":"crossref","unstructured":"D. Szklarczyk\n                      et al\n                      , The STRING database in 2021: Customizable protein\u2013protein networks, and functional characterization of user-uploaded gene\/measurement sets,\n                      49\n                      :D605\u2013D612, 2021, https:\/\/academic.oup.com\/nar\/article\/49\/D1\/D605\/6006194.","DOI":"10.1093\/nar\/gkaa1074"},{"key":"S0219720026500046BIB018","doi-asserted-by":"crossref","unstructured":"P. Jones\n                      et al\n                      , InterProScan 5: Genome-scale protein function classification,\n                      30\n                      (9):1236\u20131240, 2014, https:\/\/academic.oup.com\/bioinformatics\/article\/30\/9\/1236\/237988.","DOI":"10.1093\/bioinformatics\/btu031"},{"key":"S0219720026500046BIB019","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-1037-6"},{"key":"S0219720026500046BIB020","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-019-1835-8"},{"key":"S0219720026500046BIB021","doi-asserted-by":"publisher","DOI":"10.1093\/bioadv\/vbae043"},{"key":"S0219720026500046BIB022","doi-asserted-by":"crossref","unstructured":"W. T. Clark and P. Radivojac, Information-theoretic evaluation of predicted ontological annotations,\n                      29\n                      (13):153\u2013161, 2013, https:\/\/academic.oup.com\/bioinformatics\/article\/29\/13\/i53\/195366.","DOI":"10.1093\/bioinformatics\/btt228"}],"container-title":["Journal of Bioinformatics and Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0219720026500046","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T07:38:48Z","timestamp":1776757128000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0219720026500046"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":22,"journal-issue":{"issue":"02","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1142\/S0219720026500046"],"URL":"https:\/\/doi.org\/10.1142\/s0219720026500046","relation":{},"ISSN":["0219-7200","1757-6334"],"issn-type":[{"value":"0219-7200","type":"print"},{"value":"1757-6334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"article-number":"2650004"}}