{"id":"https://openalex.org/W4415904258","doi":"https://doi.org/10.3389/fbinf.2025.1684042","title":"ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models","display_name":"ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models","publication_year":2025,"publication_date":"2025-11-05","ids":{"openalex":"https://openalex.org/W4415904258","doi":"https://doi.org/10.3389/fbinf.2025.1684042","pmid":"https://pubmed.ncbi.nlm.nih.gov/41268176"},"language":"en","primary_location":{"id":"doi:10.3389/fbinf.2025.1684042","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fbinf.2025.1684042","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1684042/pdf","source":{"id":"https://openalex.org/S4210219554","display_name":"Frontiers in Bioinformatics","issn_l":"2673-7647","issn":["2673-7647"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://public-pages-files-2025.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1684042/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111395756","display_name":"Piyachat Udomwong","orcid":null},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Piyachat Udomwong","raw_affiliation_strings":["International College of Digital Innovation, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"International College of Digital Innovation, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076649138","display_name":"Thanathat Pamonsupornwichit","orcid":null},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Thanathat Pamonsupornwichit","raw_affiliation_strings":["Center of Biomolecular Therapy and Diagnostic, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Center of Biomolecular Therapy and Diagnostic, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003046277","display_name":"Kanchanok Kodchakorn","orcid":"https://orcid.org/0000-0002-9250-661X"},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Kanchanok Kodchakorn","raw_affiliation_strings":["Department of Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand","Office of Research Administration, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]},{"raw_affiliation_string":"Office of Research Administration, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044653763","display_name":"Chatchai Tayapiwatana","orcid":"https://orcid.org/0000-0003-2827-7995"},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Chatchai Tayapiwatana","raw_affiliation_strings":["Center of Biomolecular Therapy and Diagnostic, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand","Division of Clinical Immunology, Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Center of Biomolecular Therapy and Diagnostic, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]},{"raw_affiliation_string":"Division of Clinical Immunology, Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044653763","https://openalex.org/A5111395756"],"corresponding_institution_ids":["https://openalex.org/I48076826"],"apc_list":{"value":1900,"currency":"USD","value_usd":1900},"apc_paid":{"value":1900,"currency":"USD","value_usd":1900},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45592681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"1684042","last_page":"1684042"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11016","display_name":"Monoclonal and Polyclonal Antibodies Research","score":0.8754000067710876,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11016","display_name":"Monoclonal and Polyclonal Antibodies Research","score":0.8754000067710876,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.10719999670982361,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.0032999999821186066,"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/paratope","display_name":"Paratope","score":0.7093999981880188},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6330999732017517},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.599399983882904},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5360000133514404},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4205999970436096},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4066999852657318},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.38190001249313354}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817000150680542},{"id":"https://openalex.org/C9086966","wikidata":"https://www.wikidata.org/wiki/Q489135","display_name":"Paratope","level":4,"score":0.7093999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6481999754905701},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6330999732017517},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.599399983882904},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38839998841285706},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.38519999384880066},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C36394416","wikidata":"https://www.wikidata.org/wiki/Q949267","display_name":"Immunoglobulin light chain","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fbinf.2025.1684042","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fbinf.2025.1684042","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1684042/pdf","source":{"id":"https://openalex.org/S4210219554","display_name":"Frontiers in Bioinformatics","issn_l":"2673-7647","issn":["2673-7647"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41268176","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41268176","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":"Frontiers in bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:a84cc3985b0b4e9e987f88e3597a3a4f","is_oa":true,"landing_page_url":"https://doaj.org/article/a84cc3985b0b4e9e987f88e3597a3a4f","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":"Frontiers in Bioinformatics, Vol 5 (2025)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:11434940","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12626946","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/fbinf.2025.1684042","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fbinf.2025.1684042","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1684042/pdf","source":{"id":"https://openalex.org/S4210219554","display_name":"Frontiers in Bioinformatics","issn_l":"2673-7647","issn":["2673-7647"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3777918224","display_name":null,"funder_award_id":"N34E670096","funder_id":"https://openalex.org/F4320322817","funder_display_name":"National Research Council of Thailand"}],"funders":[{"id":"https://openalex.org/F4320321529","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25"},{"id":"https://openalex.org/F4320322817","display_name":"National Research Council of Thailand","ror":"https://ror.org/018wfhg78"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4415904258.pdf"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W91258909","https://openalex.org/W1019830208","https://openalex.org/W1030883578","https://openalex.org/W1501531009","https://openalex.org/W1832693441","https://openalex.org/W1855237549","https://openalex.org/W1976526581","https://openalex.org/W1981672277","https://openalex.org/W1982679430","https://openalex.org/W1997311863","https://openalex.org/W2009573319","https://openalex.org/W2017956110","https://openalex.org/W2050526879","https://openalex.org/W2064675550","https://openalex.org/W2071200955","https://openalex.org/W2091477384","https://openalex.org/W2097874743","https://openalex.org/W2110505462","https://openalex.org/W2112796928","https://openalex.org/W2117012297","https://openalex.org/W2118978333","https://openalex.org/W2130479394","https://openalex.org/W2131774270","https://openalex.org/W2150884352","https://openalex.org/W2153187042","https://openalex.org/W2163449716","https://openalex.org/W2167833742","https://openalex.org/W2288234278","https://openalex.org/W2433743436","https://openalex.org/W2572080171","https://openalex.org/W2618530766","https://openalex.org/W2767106145","https://openalex.org/W2801965704","https://openalex.org/W2905446269","https://openalex.org/W2919115771","https://openalex.org/W2962739339","https://openalex.org/W2969351103","https://openalex.org/W2971227267","https://openalex.org/W2986661129","https://openalex.org/W3007075806","https://openalex.org/W3016492430","https://openalex.org/W3096915742","https://openalex.org/W3138783506","https://openalex.org/W3156428263","https://openalex.org/W3164046276","https://openalex.org/W3177500196","https://openalex.org/W3177828909","https://openalex.org/W4226108318","https://openalex.org/W4280625391","https://openalex.org/W4308825561","https://openalex.org/W4327550249","https://openalex.org/W4404665097","https://openalex.org/W4406731637","https://openalex.org/W4407284294"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,27],"of":[2,169,190,213,234],"antibody":[3,68,202],"paratopes":[4],"is":[5,218],"a":[6,17,137,228],"critical":[7],"challenge":[8],"in":[9,61,210],"structure-limited,":[10],"high-throughput":[11],"discovery":[12],"workflows.":[13],"We":[14,54],"present":[15],"ParaDeep,":[16],"lightweight":[18],"and":[19,50,67,118,125,129,183,195,206,227],"interpretable":[20],"deep":[21],"learning":[22],"framework":[23],"for":[24,122,133,200,232],"residue-level":[25],"paratope":[26],"directly":[28],"from":[29,162],"amino":[30],"acid":[31],"sequences.":[32],"ParaDeep":[33,113,165],"integrates":[34],"bidirectional":[35],"long":[36],"short-term":[37],"memory":[38],"networks":[39],"with":[40,223],"one-dimensional":[41],"convolutional":[42,64],"layers":[43],"to":[44],"capture":[45],"both":[46],"long-range":[47],"sequence":[48,179],"context":[49],"local":[51],"binding":[52],"motifs.":[53],"systematically":[55],"evaluated":[56],"30":[57],"model":[58],"configurations":[59],"varying":[60],"encoding":[62],"schemes,":[63],"kernel":[65],"sizes,":[66],"chain":[69,76,95],"types.":[70],"In":[71],"five-fold":[72],"cross-validation,":[73],"heavy":[74,150,174],"(H)":[75],"models":[77,96],"achieved":[78],"the":[79,142,167,187,211],"highest":[80],"performance":[81,168],"(F1":[82,97],"=":[83,88,98,103,116,120,127,131],"0.856":[84],"\u00b1":[85,90,100,105],"0.014,":[86],"MCC":[87,102,119,130,139],"0.842":[89],"0.015),":[91],"outperforming":[92],"light":[93,158],"(L)":[94],"0.774":[99],"0.023,":[101],"0.772":[104],"0.022).":[106],"On":[107],"an":[108],"independent":[109],"blind":[110],"test":[111],"set,":[112],"attained":[114],"F1":[115,126],"0.723":[117],"0.685":[121],"H":[123],"chains,":[124,135],"0.607":[128],"0.587":[132],"L":[134],"representing":[136],"27%":[138],"improvement":[140],"over":[141],"sequence-based":[143,154],"baseline":[144],"Parapred.":[145],"Chain-specific":[146],"modeling":[147],"revealed":[148],"that":[149],"chains":[151,159,175],"provide":[152],"stronger":[153],"predictive":[155],"signals,":[156],"while":[157,176],"benefit":[160],"more":[161],"structural":[163,214],"context.":[164],"approaches":[166],"state-of-the-art":[170],"structure-based":[171],"methods":[172],"on":[173],"requiring":[177],"only":[178],"input,":[180],"enabling":[181],"faster":[182],"broader":[184],"applicability":[185],"without":[186],"computational":[188],"cost":[189],"3D":[191],"modeling.":[192],"Its":[193],"efficiency":[194],"scalability":[196],"make":[197],"it":[198],"well-suited":[199],"early-stage":[201],"discovery,":[203],"repertoire":[204],"profiling,":[205],"therapeutic":[207],"design,":[208],"particularly":[209],"absence":[212],"data.":[215],"The":[216],"implementation":[217],"freely":[219],"available":[220],"at":[221],"https://github.com/PiyachatU/ParaDeep,":[222],"Python":[224],"(PyTorch)":[225],"code":[226],"Google":[229],"Colab":[230],"interface":[231],"ease":[233],"use.":[235]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-11-05T00:00:00"}
