{"id":"https://openalex.org/W4414978787","doi":"https://doi.org/10.48550/arxiv.2510.05747","title":"Physicochemically Informed Dual-Conditioned Generative Model of T-Cell Receptor Variable Regions for Cellular Therapy","display_name":"Physicochemically Informed Dual-Conditioned Generative Model of T-Cell Receptor Variable Regions for Cellular Therapy","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414978787","doi":"https://doi.org/10.48550/arxiv.2510.05747"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2510.05747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.05747","pdf_url":"https://arxiv.org/pdf/2510.05747","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.05747","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101393141","display_name":"Jiahao Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jiahao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081924890","display_name":"Hongzong Li","orcid":"https://orcid.org/0000-0002-5774-7557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hongzong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021719279","display_name":"Ye\u2010Fan Hu","orcid":"https://orcid.org/0000-0002-7834-1476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Ye-Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031816818","display_name":"Jian\u2010Dong Huang","orcid":"https://orcid.org/0000-0003-0798-0147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jian-Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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/T11491","display_name":"CAR-T cell therapy research","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11491","display_name":"CAR-T cell therapy research","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11663","display_name":"Viral Infectious Diseases and Gene Expression in Insects","score":0.9140999913215637,"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/generative-grammar","display_name":"Generative grammar","score":0.7289999723434448},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.545799970626831},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5170000195503235},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47440001368522644},{"id":"https://openalex.org/keywords/t-cell-receptor","display_name":"T-cell receptor","score":0.4650000035762787},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.33550000190734863},{"id":"https://openalex.org/keywords/timeline","display_name":"Timeline","score":0.3310000002384186}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7289999723434448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5735999941825867},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5382999777793884},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5170000195503235},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4706999957561493},{"id":"https://openalex.org/C19317047","wikidata":"https://www.wikidata.org/wiki/Q412037","display_name":"T-cell receptor","level":4,"score":0.4650000035762787},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C4438859","wikidata":"https://www.wikidata.org/wiki/Q186117","display_name":"Timeline","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.3248000144958496},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.3073999881744385},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2806999981403351},{"id":"https://openalex.org/C2775905019","wikidata":"https://www.wikidata.org/wiki/Q192572","display_name":"In silico","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C170493617","wikidata":"https://www.wikidata.org/wiki/Q208467","display_name":"Receptor","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C41685203","wikidata":"https://www.wikidata.org/wiki/Q1974042","display_name":"Docking (animal)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C188280979","wikidata":"https://www.wikidata.org/wiki/Q911125","display_name":"Human leukocyte antigen","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.05747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.05747","pdf_url":"https://arxiv.org/pdf/2510.05747","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},{"id":"doi:10.48550/arxiv.2510.05747","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.05747","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.05747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.05747","pdf_url":"https://arxiv.org/pdf/2510.05747","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4414978787.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Physicochemically":[0],"informed":[1],"biological":[2],"sequence":[3,100],"generation":[4],"has":[5],"the":[6,117,121,146],"potential":[7],"to":[8,17,51,151],"accelerate":[9],"computer-aided":[10],"cellular":[11],"therapy,":[12],"yet":[13],"current":[14],"models":[15],"fail":[16],"\\emph{jointly}":[18],"ensure":[19],"novelty,":[20],"diversity,":[21],"and":[22,46,49,73,79,91,105,127],"biophysical":[23],"plausibility":[24],"when":[25],"designing":[26],"variable":[27],"regions":[28],"of":[29,99,113,123,141],"T-cell":[30],"receptors":[31],"(TCRs).":[32],"We":[33],"present":[34],"\\textbf{PhysicoGPTCR},":[35],"a":[36,70,96,110],"large":[37],"generative":[38,136],"protein":[39],"Transformer":[40],"that":[41,133],"is":[42,63],"\\emph{dual-conditioned}":[43],"on":[44,65],"peptide":[45],"HLA":[47],"context":[48,125],"trained":[50],"autoregressively":[52],"synthesise":[53],"TCR":[54,143],"sequences":[55],"while":[56,94],"embedding":[57],"residue-level":[58],"physicochemical":[59,128],"descriptors.":[60],"The":[61],"model":[62],"optimised":[64],"curated":[66],"TCR--peptide--HLA":[67],"triples":[68],"with":[69],"maximum-likelihood":[71],"objective":[72],"compared":[74],"against":[75],"ANN,":[76],"GPTCR,":[77],"LSTM,":[78],"VAE":[80],"baselines.":[81],"Across":[82],"multiple":[83],"neoantigen":[84],"benchmarks,":[85],"PhysicoGPTCR":[86],"substantially":[87],"improves":[88],"edit-distance,":[89],"similarity,":[90],"longest-common-subsequence":[92],"scores,":[93],"populating":[95],"broader":[97],"region":[98],"space.":[101],"Blind":[102],"in-silico":[103],"docking":[104],"structural":[106],"modelling":[107,137],"further":[108],"reveal":[109],"higher":[111],"proportion":[112],"binding-competent":[114],"clones":[115],"than":[116],"strongest":[118],"baseline,":[119],"validating":[120],"benefit":[122],"explicit":[124],"conditioning":[126],"awareness.":[129],"Experimental":[130],"results":[131],"demonstrate":[132],"dual-conditioned,":[134],"physics-grounded":[135],"enables":[138],"end-to-end":[139],"design":[140],"functional":[142],"candidates,":[144],"reducing":[145],"discovery":[147],"timeline":[148],"from":[149],"months":[150],"minutes":[152],"without":[153],"sacrificing":[154],"wet-lab":[155],"verifiability.":[156]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
