{"id":"https://openalex.org/W7126089568","doi":"https://doi.org/10.1109/bibm66473.2025.11356399","title":"scDDT: A Feature-Decoupling Conditional Diffusion Framework for Single-Cell Cross-Modality Translation","display_name":"scDDT: A Feature-Decoupling Conditional Diffusion Framework for Single-Cell Cross-Modality Translation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126089568","doi":"https://doi.org/10.1109/bibm66473.2025.11356399"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111064602","display_name":"Jialiang Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialiang Xue","raw_affiliation_strings":["School of Information Engineering, Ningxia University,Yinchuan,China,750021"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Ningxia University,Yinchuan,China,750021","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102583006","display_name":"Junlei Zhou","orcid":"https://orcid.org/0000-0001-8781-0628"},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlei Zhou","raw_affiliation_strings":["School of Information Engineering, Ningxia University,Yinchuan,China,750021"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Ningxia University,Yinchuan,China,750021","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121115469","display_name":"Yang E. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["School of Information Engineering, Ningxia University,Yinchuan,China,750021"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Ningxia University,Yinchuan,China,750021","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114025829","display_name":"Zhenhua Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Yu","raw_affiliation_strings":["School of Information Engineering, Ningxia University,Yinchuan,China,750021"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Ningxia University,Yinchuan,China,750021","institution_ids":["https://openalex.org/I21642278"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21642278"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1391","last_page":"1396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9689000248908997,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9689000248908997,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.008700000122189522,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00430000014603138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.8198000192642212},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5752999782562256},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.3873000144958496},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.37860000133514404},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.3601999878883362},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.3582000136375427},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.35040000081062317}],"concepts":[{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.8198000192642212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.63919997215271},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5752999782562256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4677000045776367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41339999437332153},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.385699987411499},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35040000081062317},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3296999931335449},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25940001010894775},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5103070055","display_name":null,"funder_award_id":"2023AAC05006","funder_id":"https://openalex.org/F4320322877","funder_display_name":"Natural Science Foundation of Ningxia Province"}],"funders":[{"id":"https://openalex.org/F4320322877","display_name":"Natural Science Foundation of Ningxia Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2205615102","https://openalex.org/W2739492614","https://openalex.org/W2752426001","https://openalex.org/W2897249806","https://openalex.org/W2901006884","https://openalex.org/W2912390237","https://openalex.org/W2950779253","https://openalex.org/W2951506174","https://openalex.org/W2965985232","https://openalex.org/W3013823153","https://openalex.org/W3095452393","https://openalex.org/W3133082627","https://openalex.org/W3144696998","https://openalex.org/W3201518044","https://openalex.org/W3214158901","https://openalex.org/W4214673148","https://openalex.org/W4280598116","https://openalex.org/W4285175832","https://openalex.org/W4313527389","https://openalex.org/W4367313533","https://openalex.org/W4378212624","https://openalex.org/W4378649427","https://openalex.org/W4391167460","https://openalex.org/W4394011009","https://openalex.org/W4400266097","https://openalex.org/W4401093660","https://openalex.org/W4404399964","https://openalex.org/W4410855348","https://openalex.org/W4412152249"],"related_works":[],"abstract_inverted_index":{"Single-cell":[0],"multi-modal":[1],"analysis":[2,125],"has":[3],"made":[4],"significant":[5],"progress":[6],"in":[7,24,99,126],"recent":[8],"years.":[9],"However,":[10],"the":[11,53],"translation":[12,76,101],"and":[13,29,57,62,65,108,113],"generation":[14,44],"of":[15],"data":[16,25,43],"across":[17],"modalities":[18,78],"remain":[19],"challenging":[20],"due":[21],"to":[22,72],"differences":[23],"types,":[26],"measurement":[27],"scales,":[28],"inherent":[30],"noise.":[31],"In":[32],"this":[33],"study,":[34],"we":[35],"propose":[36],"a":[37,47,120],"novel":[38],"method":[39,54],"for":[40,111,123],"single-cell":[41,127],"cross-modality":[42,100,124],"based":[45],"on":[46,86],"feature-decoupling":[48],"conditional":[49,69],"diffusion":[50,70],"framework.":[51],"Specifically,":[52],"decouples":[55],"modality-unique":[56],"common":[58],"features":[59],"using":[60],"modality-specific":[61],"shared":[63],"encoders,":[64],"then":[66],"leverages":[67],"two":[68],"models":[71],"enable":[73],"accurate":[74],"bidirectional":[75],"between":[77],"without":[79],"requiring":[80],"prior":[81],"cell-type":[82],"annotations.":[83],"Experimental":[84],"results":[85],"four":[87],"real":[88],"datasets":[89],"demonstrate":[90],"that":[91],"our":[92],"approach":[93],"significantly":[94],"outperforms":[95],"existing":[96],"state-of-the-art":[97],"methods":[98],"tasks,":[102],"achieving":[103],"higher":[104],"Pearson":[105],"correlation":[106],"coefficients":[107],"AUROC":[109],"scores":[110],"RNA":[112],"ATAC":[114],"generation.":[115],"The":[116],"proposed":[117],"framework":[118],"offers":[119],"promising":[121],"solution":[122],"research.":[128]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}