{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T14:20:21Z","timestamp":1787581221115,"version":"build-2736575974"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T00:00:00Z","timestamp":1786147200000},"content-version":"vor","delay-in-days":219,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Health","award":["R01GM145937"],"award-info":[{"award-number":["R01GM145937"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DBI2308699"],"award-info":[{"award-number":["DBI2308699"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Protein function prediction is a challenging task and an open problem in computational biology. The Critical Assessment of protein Function Annotation (CAFA) is a triennial, community-driven initiative that provides an independent, large-scale evaluation of computational methods for protein function prediction through time-delayed benchmarking experiments. CAFA has played a key role in highlighting high-performing methodologies and fostering detailed analysis and exchange of ideas. However, outside the periodic CAFA challenges, there is no platform for the continuous evaluation of newly developed methods and tracking performance as function annotations accumulate.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here we introduce the Longitudinal Assessment of Protein Function Annotation Models server (LAFA) as a persistent benchmarking system for protein function prediction methods. LAFA provides a continuous evaluation of containerized function prediction methods, enabling up-to-date and robust comparative assessment of method performance under evolving ground truth. LAFA accelerates methodological iteration, supports reproducibility, and offers a more dynamic and fine-grained view of progress in protein function prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Code and Data Availability<\/jats:title>\n                    <jats:p>LAFA is available at https:\/\/functionbench.net\/. Detailed evaluation results can be found at https:\/\/github.com\/FriedbergLab\/CAFA_forever.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioadv\/vbag221","type":"journal-article","created":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T11:49:03Z","timestamp":1785930543000},"source":"Crossref","is-referenced-by-count":0,"title":["LAFA: a framework for reproducible\n                    <u>l<\/u>\n                    ongitudinal\n                    <u>a<\/u>\n                    ssessment of protein\n                    <u>f<\/u>\n                    unction\n                    <u>a<\/u>\n                    nnotation models"],"prefix":"10.1093","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0154-076X","authenticated-orcid":false,"given":"An","family":"Phan","sequence":"first","affiliation":[{"name":"Iowa State University Program in Bioinformatics and Computational Biology, , Ames, IA 50011,","place":["United States"]},{"name":"Iowa State University Department of Veterinary Microbiology and Preventive Medicine, , Ames, IA 50011,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7864-826X","authenticated-orcid":false,"given":"Yanli","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Missouri Department of Electrical Engineering and Computer Science, , Columbia, MO 65211,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frimpong","family":"Boadu","sequence":"additional","affiliation":[{"name":"Microsoft Corporation Software Engineering, , Redmond, WA 98052,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0305-2853","authenticated-orcid":false,"given":"Jianlin","family":"Cheng","sequence":"additional","affiliation":[{"name":"University of Missouri Department of Electrical Engineering and Computer Science, , Columbia, MO 65211,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6769-0793","authenticated-orcid":false,"given":"Predrag","family":"Radivojac","sequence":"additional","affiliation":[{"name":"Northeastern University Khoury College of Computer Sciences, , Boston, MA 02115,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1789-8000","authenticated-orcid":false,"given":"Iddo","family":"Friedberg","sequence":"additional","affiliation":[{"name":"Iowa State University Department of Veterinary Microbiology and Preventive Medicine, , Ames, IA 50011,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,7]]},"reference":[{"key":"2026082409220688700_vbag221-B1","doi-asserted-by":"crossref","first-page":"D609","DOI":"10.1093\/nar\/gkae1010","article-title":"Uniprot: the universal protein knowledgebase in 2025","volume":"53","author":"Bateman","year":"2025","journal-title":"Nucleic Acids Res"},{"key":"2026082409220688700_vbag221-B2","doi-asserted-by":"crossref","first-page":"vbae120","DOI":"10.1093\/bioadv\/vbae120","article-title":"Improving protein function prediction by learning and integrating representations of protein sequences and function labels","volume":"4","author":"Boadu","year":"2024","journal-title":"Bioinform Adv"},{"key":"2026082409220688700_vbag221-B3","doi-asserted-by":"publisher","author":"Boadu","year":"2025","DOI":"10.1101\/2025.05.09.653226"},{"key":"2026082409220688700_vbag221-B4","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1002\/prot.25832","article-title":"Machine learning techniques for protein function prediction","volume":"88","author":"Bonetta","year":"2020","journal-title":"Proteins Struct Funct 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