{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:57:17Z","timestamp":1778227037127,"version":"3.51.4"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2018,9,6]],"date-time":"2018-09-06T00:00:00Z","timestamp":1536192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM123055"],"award-info":[{"award-number":["R01GM123055"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DBI1262189"],"award-info":[{"award-number":["DBI1262189"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS1614777"],"award-info":[{"award-number":["DMS1614777"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Biological experiments including proteomics and transcriptomics approaches often reveal sets of proteins that are most likely to be involved in a disease\/disorder. To understand the functional nature of a set of proteins, it is important to capture the function of the proteins as a group, even in cases where function of individual proteins is not known. In this work, we propose a model that takes groups of proteins found to work together in a certain biological context, integrates them into functional relevance networks, and subsequently employs an iterative inference on graphical models to identify group functions of the proteins, which are then extended to predict function of individual proteins.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The proposed algorithm, iterative group function prediction (iGFP), depicts proteins as a graph that represents functional relevance of proteins considering their known functional, proteomics and transcriptional features. Proteins in the graph will be clustered into groups by their mutual functional relevance, which is iteratively updated using a probabilistic graphical model, the conditional random field. iGFP showed robust accuracy even when substantial amount of GO annotations were missing. The perspective of \u2018group\u2019 function annotation opens up novel approaches for understanding functional nature of proteins in biological systems.<\/jats:p>\n                  <jats:p>Availability and implementation: http:\/\/kiharalab.org\/iGFP\/<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty787","type":"journal-article","created":{"date-parts":[[2018,9,4]],"date-time":"2018-09-04T19:27:16Z","timestamp":1536089236000},"page":"1388-1394","source":"Crossref","is-referenced-by-count":8,"title":["Prediction of protein group function by iterative classification on functional relevance network"],"prefix":"10.1093","volume":"35","author":[{"given":"Ishita K","family":"Khan","sequence":"first","affiliation":[{"name":"Department of Computer Science, Purdue University, West Lafayette, IN, USA"},{"name":"eBay Search Science, San Jose, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aashish","family":"Jain","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Purdue University, West Lafayette, IN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reda","family":"Rawi","sequence":"additional","affiliation":[{"name":"Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar"},{"name":"Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Halima","family":"Bensmail","sequence":"additional","affiliation":[{"name":"Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4091-6614","authenticated-orcid":false,"given":"Daisuke","family":"Kihara","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Purdue University, West Lafayette, IN, USA"},{"name":"Department of Biological Sciences, Purdue University, West Lafayette, IN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,9,6]]},"reference":[{"key":"2023012810013565800_bty787-B1","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic local alignment search tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J. Mol. Biol"},{"key":"2023012810013565800_bty787-B2","doi-asserted-by":"crossref","first-page":"e26277","DOI":"10.1371\/journal.pone.0026277","article-title":"A new methodology to associate SNPs with human diseases according to their pathway related context","volume":"6","author":"Bakir-Gungor","year":"2011","journal-title":"PLoS One"},{"key":"2023012810013565800_bty787-B3","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1038\/nmeth.2561","article-title":"mentha: a resource for browsing integrated protein-interaction networks","volume":"10","author":"Calderone","year":"2013","journal-title":"Nat. Methods"},{"key":"2023012810013565800_bty787-B4","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.ymeth.2015.09.011","article-title":"Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks","volume":"93","author":"Cao","year":"2016","journal-title":"Methods"},{"key":"2023012810013565800_bty787-B5","doi-asserted-by":"crossref","first-page":"1732","DOI":"10.3390\/molecules22101732","article-title":"ProLanGO: protein function prediction using neural machine translation based on a recurrent neural network","volume":"22","author":"Cao","year":"2017","journal-title":"Molecules"},{"key":"2023012810013565800_bty787-B6","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1093\/bioinformatics\/btp309","article-title":"ESG: extended similarity group method for automated protein function prediction","volume":"25","author":"Chitale","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012810013565800_bty787-B7","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1093\/bioinformatics\/btl145","article-title":"Exploiting indirect neighbours and topological weight to predict protein function from protein-protein interactions","volume":"22","author":"Chua","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012810013565800_bty787-B8","doi-asserted-by":"crossref","first-page":"498.","DOI":"10.1186\/1471-2105-11-498","article-title":"Automatic, context-specific generation of Gene Ontology slims","volume":"11","author":"Davis","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023012810013565800_bty787-B9","doi-asserted-by":"crossref","first-page":"D190","DOI":"10.1093\/nar\/gkw1107","article-title":"InterPro in 2017-beyond protein family and domain annotations","volume":"45","author":"Finn","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023012810013565800_bty787-B10","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1126\/science.1136800","article-title":"Clustering by passing messages between data points","volume":"315","author":"Frey","year":"2007","journal-title":"Science"},{"key":"2023012810013565800_bty787-B11","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1007\/978-3-642-39159-0_17","article-title":"Conditional Random Fields for Protein Function Prediction","volume":"7986","author":"Gehrmann","year":"2013","journal-title":"Pattern Recognit. Bioinform"},{"key":"2023012810013565800_bty787-B12","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1002\/prot.22172","article-title":"PFP: automated prediction of gene ontology functional annotations with confidence scores using protein sequence data","volume":"74","author":"Hawkins","year":"2009","journal-title":"Proteins"},{"key":"2023012810013565800_bty787-B13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S0219720007002503","article-title":"Function prediction of uncharacterized proteins","volume":"5","author":"Hawkins","year":"2007","journal-title":"J. Bioinform. Comput. Biol"},{"key":"2023012810013565800_bty787-B14","doi-asserted-by":"crossref","first-page":"D353","DOI":"10.1093\/nar\/gkw1092","article-title":"KEGG: new perspectives on genomes, pathways, diseases and drugs","volume":"45","author":"Kanehisa","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023012810013565800_bty787-B15","doi-asserted-by":"crossref","first-page":"W89","DOI":"10.1093\/nar\/gki414","article-title":"ProFunc: a server for predicting protein function from 3D structure","volume":"33","author":"Laskowski","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"2023012810013565800_bty787-B16","doi-asserted-by":"crossref","first-page":"D82","DOI":"10.1093\/nar\/gku1163","article-title":"COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems","volume":"43","author":"Okamura","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023012810013565800_bty787-B17","doi-asserted-by":"crossref","first-page":"2444","DOI":"10.1073\/pnas.85.8.2444","article-title":"Improved tools for biological sequence comparison","volume":"85","author":"Pearson","year":"1988","journal-title":"Proc. Natl. Acad. Sci. U S A"},{"key":"2023012810013565800_bty787-B18","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1038\/nmeth.2340","article-title":"A large-scale evaluation of computational protein function prediction","volume":"10","author":"Radivojac","year":"2013","journal-title":"Nat. Methods"},{"key":"2023012810013565800_bty787-B19","doi-asserted-by":"crossref","first-page":"302.","DOI":"10.1186\/1471-2105-7-302","article-title":"A new measure for functional similarity of gene products based on Gene Ontology","volume":"7","author":"Schlicker","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023012810013565800_bty787-B20","doi-asserted-by":"crossref","first-page":"88.","DOI":"10.1038\/msb4100129","article-title":"Network-based prediction of protein function","volume":"3","author":"Sharan","year":"2007","journal-title":"Mol. Syst. Biol"},{"key":"2023012810013565800_bty787-B21","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc. Natl. Acad. Sci. U S A"},{"key":"2023012810013565800_bty787-B22","doi-asserted-by":"crossref","first-page":"D362","DOI":"10.1093\/nar\/gkw937","article-title":"The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible","volume":"45","author":"Szklarczyk","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023012810013565800_bty787-B23","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1002\/9781118617151.ch09","volume-title":"Handbook of Biological Knowledge Discovery","author":"Tang","year":"2013"},{"key":"2023012810013565800_bty787-B24","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/S0168-9525(03)00056-8","article-title":"Predicting gene function by conserved co-expression","volume":"19","author":"van Noort","year":"2003","journal-title":"Trends Genet"},{"key":"2023012810013565800_bty787-B25","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/nmeth.2810","article-title":"Similarity network fusion for aggregating data types on a genomic scale","volume":"11","author":"Wang","year":"2014","journal-title":"Nat. Methods"},{"key":"2023012810013565800_bty787-B26","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1093\/bioinformatics\/btn037","article-title":"ConFunc\u2014functional annotation in the twilight zone","volume":"24","author":"Wass","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012810013565800_bty787-B27","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1093\/bioinformatics\/btu724","article-title":"Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0","volume":"31","author":"Zhu","year":"2015","journal-title":"Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/8\/1388\/48940642\/bioinformatics_35_8_1388.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/8\/1388\/48940642\/bioinformatics_35_8_1388.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,28]],"date-time":"2023-01-28T10:09:34Z","timestamp":1674900574000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/35\/8\/1388\/5091331"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2018,9,6]]},"references-count":27,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2019,4,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bty787","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,4,15]]},"published":{"date-parts":[[2018,9,6]]}}}