{"id":"https://openalex.org/W2924319274","doi":"https://doi.org/10.1101/590620","title":"Deep convolutional neural networks for predicting the quality of single protein structural models","display_name":"Deep convolutional neural networks for predicting the quality of single protein structural models","publication_year":2019,"publication_date":"2019-03-28","ids":{"openalex":"https://openalex.org/W2924319274","doi":"https://doi.org/10.1101/590620","mag":"2924319274"},"language":"en","primary_location":{"id":"doi:10.1101/590620","doi":"https://doi.org/10.1101/590620","is_oa":true,"landing_page_url":"https://doi.org/10.1101/590620","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2019/03/28/590620.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.biorxiv.org/content/biorxiv/early/2019/03/28/590620.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022495891","display_name":"Jie Hou","orcid":"https://orcid.org/0000-0002-8584-5154","observed_orcids":["https://orcid.org/0000-0002-8584-5154","https://orcid.org/0009-0003-2250-0532"]},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Hou","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 65211, USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 652, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 65211, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 652, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085487073","display_name":"Renzhi Cao","orcid":"https://orcid.org/0000-0002-8345-343X","observed_orcids":["https://orcid.org/0000-0002-8345-343X"]},"institutions":[{"id":"https://openalex.org/I60065076","display_name":"Pacific Lutheran University","ror":"https://ror.org/01vh5nd96","country_code":"US","type":"education","lineage":["https://openalex.org/I60065076"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Renzhi Cao","raw_affiliation_strings":["Department of Computer Science, Pacific Lutheran University, WA 98447, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Pacific Lutheran University, WA 98447, USA","institution_ids":["https://openalex.org/I60065076"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044354277","display_name":"Jianlin Jack Cheng","orcid":"https://orcid.org/0000-0003-0305-2853","observed_orcids":["https://orcid.org/0000-0003-0305-2853"]},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jianlin Cheng","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 65211, USA","Informatics Institute, University of Missouri, Columbia, Missouri, 65211, USA","Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 652, USA","Informatics Institute, University of Missouri, Columbia, Missouri, 6511, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 65211, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Informatics Institute, University of Missouri, Columbia, Missouri, 65211, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, 652, USA","institution_ids":["https://openalex.org/I76835614"]},{"raw_affiliation_string":"Informatics Institute, University of Missouri, Columbia, Missouri, 6511, USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044354277"],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.0044999998062849045,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11162","display_name":"Enzyme Structure and Function","score":0.004399999976158142,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/protein-structure-quality-assessment","display_name":"protein structure quality assessment","score":0.8339999914169312},{"id":"https://openalex.org/keywords/1d-convolutional-neural-network","display_name":"1D convolutional neural network","score":0.8190000057220459},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"multi-task learning","score":0.9629999995231628},{"id":"https://openalex.org/keywords/solvent-accessibility","display_name":"solvent accessibility","score":0.6589999794960022},{"id":"https://openalex.org/keywords/caspase-11","display_name":"caspase-11","score":0.5979999899864197},{"id":"https://openalex.org/keywords/caspase-12","display_name":"caspase-12","score":0.996999979019165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7524393796920776},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7041891813278198},{"id":"https://openalex.org/C66153294","wikidata":"https://www.wikidata.org/wiki/Q899291","display_name":"CASP","level":4,"score":0.6961991786956787},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.6884962320327759},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6691703796386719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6182624101638794},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5861872434616089},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.5732972621917725},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5443283319473267},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5213064551353455},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4742518961429596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45487484335899353},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.4209043085575104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3402130603790283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33858972787857056},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.30414238572120667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27814361453056335},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0781329870223999},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06811931729316711},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1101/590620","doi":"https://doi.org/10.1101/590620","is_oa":true,"landing_page_url":"https://doi.org/10.1101/590620","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2019/03/28/590620.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.1101/590620","doi":"https://doi.org/10.1101/590620","is_oa":true,"landing_page_url":"https://doi.org/10.1101/590620","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2019/03/28/590620.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G254862159","display_name":"III: Medium: Collaborative Research: Guiding Exploration of Protein Structure Spaces with Deep Learning","funder_award_id":"1763246","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G613702328","display_name":"ABI Innovation:  Deep learning methods for protein bioinformatics","funder_award_id":"1759934","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7450496187","display_name":"Distance-based ab initio protein structure prediction","funder_award_id":"R01GM093123","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G946059479","display_name":null,"funder_award_id":"R01GM093123","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2924319274.pdf","grobid_xml":"https://content.openalex.org/works/W2924319274.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W1763545885","https://openalex.org/W1836465849","https://openalex.org/W1843970493","https://openalex.org/W1965615878","https://openalex.org/W1983497040","https://openalex.org/W1989777815","https://openalex.org/W1999613945","https://openalex.org/W2002129624","https://openalex.org/W2008505479","https://openalex.org/W2031721366","https://openalex.org/W2033357321","https://openalex.org/W2075095565","https://openalex.org/W2093567555","https://openalex.org/W2096004651","https://openalex.org/W2107253825","https://openalex.org/W2109801072","https://openalex.org/W2110483430","https://openalex.org/W2116672918","https://openalex.org/W2117451312","https://openalex.org/W2119550029","https://openalex.org/W2120615054","https://openalex.org/W2123085274","https://openalex.org/W2125673699","https://openalex.org/W2130672128","https://openalex.org/W2131474431","https://openalex.org/W2138755951","https://openalex.org/W2140574901","https://openalex.org/W2145991251","https://openalex.org/W2150831049","https://openalex.org/W2158714788","https://openalex.org/W2161151688","https://openalex.org/W2243910093","https://openalex.org/W2287165934","https://openalex.org/W2299697047","https://openalex.org/W2385735394","https://openalex.org/W2411608355","https://openalex.org/W2418704427","https://openalex.org/W2514534732","https://openalex.org/W2565608178","https://openalex.org/W2577772780","https://openalex.org/W2594725344","https://openalex.org/W2606314633","https://openalex.org/W2622049782","https://openalex.org/W2949117887","https://openalex.org/W2949867299","https://openalex.org/W2951621517","https://openalex.org/W6833262898"],"related_works":["https://openalex.org/W2784883284","https://openalex.org/W2971780522","https://openalex.org/W3113027540","https://openalex.org/W3109027947","https://openalex.org/W2805338223","https://openalex.org/W2514534732","https://openalex.org/W3015047409","https://openalex.org/W2807524936","https://openalex.org/W4225533038","https://openalex.org/W7002458442"],"abstract_inverted_index":{"Abstract":[0],"Predicting":[1],"the":[2,37,127,131,142,153,163,181],"global":[3,56,176,182],"quality":[4,8,40,57,165,177,183],"and":[5,21,55,69,80,86,122,139,146,175,189],"local":[6,39,54,174],"(residual-specific)":[7],"of":[9,41,77,89,93,112,130,135,144,155,191],"a":[10,28,42,60,90,109],"single":[11,43],"protein":[12,18,44,91,133],"structural":[13,70,128],"model":[14,45,92],"is":[15,103,160],"important":[16],"for":[17],"structure":[19,79],"prediction":[20,184],"application.":[22],"In":[23],"this":[24],"work,":[25],"we":[26],"developed":[27],"deep":[29,157],"one-dimensional":[30],"convolutional":[31],"neural":[32],"network":[33],"(1DCNN)":[34],"that":[35,152,172],"predicts":[36],"absolute":[38],"as":[46,48,96,115],"well":[47],"two":[49],"1DCNNs":[50],"to":[51,98,162],"predict":[52,99],"both":[53],"simultaneously":[58],"through":[59],"novel":[61],"multi-task":[62],"learning":[63,158],"framework.":[64],"The":[65,149,186],"networks":[66],"accept":[67],"sequential":[68],"features":[71,114],"(i.e.":[72],"amino":[73],"acid":[74],"sequence,":[75],"agreement":[76],"secondary":[78],"solvent":[81],"accessibilities,":[82],"residual":[83],"disorder":[84],"properties":[85],"Rosetta":[87],"energies)":[88],"any":[94],"size":[95],"input":[97],"its":[100],"quality,":[101],"which":[102],"different":[104],"from":[105],"existing":[106],"methods":[107,119,159,193],"using":[108],"fixed":[110],"number":[111],"hand-crafted":[113],"input.":[116],"Our":[117,168],"three":[118],"(InteractQA-net,":[120],"JointQA-net":[121],"LocalQA-net)":[123],"were":[124],"trained":[125],"on":[126,141],"models":[129,143],"single-domain":[132],"targets":[134],"CASP8,":[136],"9,":[137],"10":[138],"evaluated":[140],"CASP11":[145],"CASP12":[147],"targets.":[148],"results":[150],"show":[151],"performance":[154],"our":[156,192],"comparable":[161],"state-of-the-art":[164],"assessment":[166],"methods.":[167],"study":[169],"also":[170],"demonstrates":[171],"combining":[173],"predictions":[178],"together":[179],"improves":[180],"accuracy.":[185],"source":[187],"code":[188],"executable":[190],"are":[194],"available":[195],"at:":[196],"https://github.com/multicom-toolbox/DeepCovQA":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4}],"updated_date":"2026-10-15T10:00:46.086208","created_date":"2019-04-01T00:00:00"}