{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:51:30Z","timestamp":1778226690525,"version":"3.51.4"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"W1","license":[{"start":{"date-parts":[[2019,5,25]],"date-time":"2019-05-25T00:00:00Z","timestamp":1558742400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01-GM100701"],"award-info":[{"award-number":["R01-GM100701"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35-GM126985"],"award-info":[{"award-number":["R35-GM126985"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper presents a new fast and accurate web service for protein model quality analysis, called PSICA (Protein Structural Information Conformity Analysis). It is designed to evaluate how much a tertiary model of a given protein primary sequence conforms to the known protein structures of similar protein sequences, and to evaluate the quality of predicted protein models. PSICA implements the MUfoldQA_S method, an efficient state-of-the-art protein model quality assessment (QA) method. In CASP12, MUfoldQA_S ranked No. 1 in the protein model QA select-20 category in terms of the difference between the predicted and true GDT-TS value of each model. For a given predicted 3D model, PSICA generates (i) predicted global GDT-TS value; (ii) interactive comparison between the model and other known protein structures; (iii) visualization of the predicted local quality of the model; and (iv) JSmol rendering of the model. Additionally, PSICA implements MUfoldQA_C, a new consensus method based on MUfoldQA_S. In CASP12, MUfoldQA_C ranked No. 1 in top 1 model GDT-TS loss on the select-20 QA category and No. 2 in the average difference between the predicted and true GDT-TS value of each model for both select-20 and best-150 QA categories. The PSICA server is freely available at http:\/\/qas.wangwb.com\/\u223cwwr34\/mufoldqa\/index.html.<\/jats:p>","DOI":"10.1093\/nar\/gkz402","type":"journal-article","created":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T11:26:10Z","timestamp":1556796370000},"page":"W443-W450","source":"Crossref","is-referenced-by-count":15,"title":["PSICA: a fast and accurate web service for protein model quality analysis"],"prefix":"10.1093","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8275-1067","authenticated-orcid":false,"given":"Wenbo","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaoyu","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junlin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"},{"name":"Christopher S. 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