{"id":"https://openalex.org/W4389486963","doi":"https://doi.org/10.1186/s13321-023-00788-8","title":"HybridGCN for protein solubility prediction with adaptive weighting of multiple features","display_name":"HybridGCN for protein solubility prediction with adaptive weighting of multiple features","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4389486963","doi":"https://doi.org/10.1186/s13321-023-00788-8","pmid":"https://pubmed.ncbi.nlm.nih.gov/38066570"},"language":"en","primary_location":{"id":"doi:10.1186/s13321-023-00788-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00788-8","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00788-8","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00788-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100336451","display_name":"Long Chen","orcid":"https://orcid.org/0009-0000-0045-6524"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Long Chen","raw_affiliation_strings":["Readline Intelligence, Leeds, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Readline Intelligence, Leeds, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101437076","display_name":"Rining Wu","orcid":"https://orcid.org/0000-0002-8834-9316"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rining Wu","raw_affiliation_strings":["Readline Intelligence, Leeds, United Kingdom","School of Computing, University of Leeds, Leeds, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Readline Intelligence, Leeds, United Kingdom","institution_ids":[]},{"raw_affiliation_string":"School of Computing, University of Leeds, Leeds, United Kingdom","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017474350","display_name":"Feixiang Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feixiang Zhou","raw_affiliation_strings":["Readline Intelligence, Leeds, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Readline Intelligence, Leeds, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108048500","display_name":"Huifeng Zhang","orcid":"https://orcid.org/0000-0002-3764-6791"},"institutions":[{"id":"https://openalex.org/I188950975","display_name":"GlaxoSmithKline (United Kingdom)","ror":"https://ror.org/01xsqw823","country_code":"GB","type":"company","lineage":["https://openalex.org/I188950975"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huifeng Zhang","raw_affiliation_strings":["Readline Intelligence, Leeds, United Kingdom. ben.zhang@readlineint.com","Readline Intelligence, Leeds, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Readline Intelligence, Leeds, United Kingdom. ben.zhang@readlineint.com","institution_ids":["https://openalex.org/I188950975"]},{"raw_affiliation_string":"Readline Intelligence, Leeds, United Kingdom","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001710920","display_name":"Jian K. Liu","orcid":"https://orcid.org/0000-0002-5391-7213"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jian K. Liu","raw_affiliation_strings":["School of Computer Science, University of Birmingham, Birmingham, United Kingdom. j.liu.22@bham.ac.uk","School of Computer Science, University of Birmingham, Birmingham, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, United Kingdom. j.liu.22@bham.ac.uk","institution_ids":["https://openalex.org/I79619799"]},{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001710920"],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":{"value":1290,"currency":"GBP","value_usd":1582},"apc_paid":{"value":1290,"currency":"GBP","value_usd":1582},"fwci":3.8919,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.94775797,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"15","issue":"1","first_page":"118","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9962000250816345,"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/T11124","display_name":"Protein purification and stability","score":0.9786999821662903,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7306768298149109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6743912696838379},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5917950868606567},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5898423194885254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5380674600601196},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4858948588371277},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47025999426841736},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44131579995155334},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3476867973804474}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306768298149109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6743912696838379},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5917950868606567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5898423194885254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5380674600601196},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4858948588371277},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47025999426841736},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44131579995155334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3476867973804474},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s13321-023-00788-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00788-8","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00788-8","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},{"id":"pmid:38066570","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38066570","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of cheminformatics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10704697","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10704697","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10704697/pdf/13321_2023_Article_788.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Cheminform","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:a22af737159e4d16b066356ed7ffdf60","is_oa":true,"landing_page_url":"https://doaj.org/article/a22af737159e4d16b066356ed7ffdf60","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-13 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13321-023-00788-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00788-8","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00788-8","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4389486963.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1588724272","https://openalex.org/W1663984431","https://openalex.org/W1976731339","https://openalex.org/W2001662797","https://openalex.org/W2067602907","https://openalex.org/W2072199556","https://openalex.org/W2083152645","https://openalex.org/W2094535327","https://openalex.org/W2102592002","https://openalex.org/W2119246926","https://openalex.org/W2133458779","https://openalex.org/W2141062474","https://openalex.org/W2147209844","https://openalex.org/W2158714788","https://openalex.org/W2164511624","https://openalex.org/W2484828460","https://openalex.org/W2557595285","https://openalex.org/W2585597953","https://openalex.org/W2607268717","https://openalex.org/W2620185010","https://openalex.org/W2622826443","https://openalex.org/W2766578745","https://openalex.org/W2794004073","https://openalex.org/W2808950571","https://openalex.org/W2897765576","https://openalex.org/W2943780190","https://openalex.org/W2963749793","https://openalex.org/W2971227267","https://openalex.org/W2979588939","https://openalex.org/W2979986977","https://openalex.org/W2983156430","https://openalex.org/W2995514860","https://openalex.org/W3109312535","https://openalex.org/W3129073614","https://openalex.org/W3139424959","https://openalex.org/W3163088702","https://openalex.org/W3166925323","https://openalex.org/W3177828909","https://openalex.org/W3186179742","https://openalex.org/W3202848468","https://openalex.org/W3216325381","https://openalex.org/W4244166797","https://openalex.org/W4288066876","https://openalex.org/W4296032638","https://openalex.org/W4306873876","https://openalex.org/W4318071656","https://openalex.org/W4319425375","https://openalex.org/W4321480048","https://openalex.org/W4375856225","https://openalex.org/W4379985112","https://openalex.org/W4384389802"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W2283145973","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2905271011","https://openalex.org/W3048601286","https://openalex.org/W3164948662"],"abstract_inverted_index":{"The":[0],"solubility":[1,38,62,94],"of":[2,12,80,100,190,202],"proteins":[3],"stands":[4],"as":[5],"a":[6,86,148,155,172],"pivotal":[7],"factor":[8],"in":[9,207],"the":[10,18,28,72,98,114,139,188,200,203,211],"realm":[11],"pharmaceutical":[13],"research":[14],"and":[15,24,50,107,120,161,167,195,214],"production.":[16],"Addressing":[17],"imperative":[19],"to":[20,54,153,182,199],"enhance":[21],"production":[22],"efficiency":[23],"curtail":[25],"experimental":[26],"costs,":[27],"demand":[29],"arises":[30],"for":[31,61,142],"computational":[32],"models":[33,49],"adept":[34],"at":[35],"accurately":[36],"predicting":[37],"based":[39],"on":[40,210],"provided":[41],"datasets.":[42,217],"Prior":[43],"investigations":[44],"have":[45,67],"leveraged":[46],"deep":[47],"learning":[48,157],"feature":[51,143,158,174,191],"engineering":[52],"techniques":[53],"distill":[55],"features":[56,75,106,119,122,132],"from":[57],"raw":[58],"protein":[59,150,165],"sequences":[60],"prediction.":[63],"However,":[64],"these":[65],"methodologies":[66],"not":[68],"thoroughly":[69],"delved":[70],"into":[71,113],"interdependencies":[73],"among":[74],"or":[76],"their":[77],"respective":[78],"magnitudes":[79],"significance.":[81],"This":[82],"study":[83],"introduces":[84],"HybridGCN,":[85],"pioneering":[87],"Hybrid":[88],"Graph":[89],"Convolutional":[90],"Network":[91],"that":[92,124],"elevates":[93],"prediction":[95],"accuracy":[96],"through":[97],"combination":[99],"diverse":[101],"features,":[102,130,185],"encompassing":[103],"sophisticated":[104],"deep-learning":[105,118,136],"classical":[108],"biophysical":[109,121,126],"features.":[110],"An":[111],"exploration":[112],"intricate":[115],"interplay":[116],"between":[117],"revealed":[123],"specific":[125],"attributes,":[127],"notably":[128],"evolutionary":[129],"complement":[131],"extracted":[133],"by":[134],"advanced":[135],"models.":[137],"Augmenting":[138],"model's":[140],"capability":[141],"representation,":[144],"we":[145,170],"employed":[146],"ESM,":[147],"substantial":[149],"language":[151],"model,":[152],"derive":[154],"zero-shot":[156],"capturing":[159],"comprehensive":[160],"pertinent":[162],"information":[163],"concerning":[164],"functions":[166],"structures.":[168],"Furthermore,":[169],"proposed":[171],"novel":[173],"fusion":[175],"module":[176],"termed":[177],"Adaptive":[178],"Feature":[179],"Re-weighting":[180],"(AFR)":[181],"integrate":[183],"multiple":[184],"thereby":[186],"enabling":[187],"fine-tuning":[189],"importance.":[192],"Ablation":[193],"experiments":[194],"comparative":[196],"analyses":[197],"attest":[198],"efficacy":[201],"HybridGCN":[204],"approach,":[205],"culminating":[206],"state-of-the-art":[208],"performances":[209],"public":[212],"eSOL":[213],"S.":[215],"cerevisiae":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":7}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}