{"id":"https://openalex.org/W4392255466","doi":"https://doi.org/10.1145/3637732.3637780","title":"HiCTF:A Transformer Model for enhancing Hi-C data resolution","display_name":"HiCTF:A Transformer Model for enhancing Hi-C data resolution","publication_year":2023,"publication_date":"2023-11-09","ids":{"openalex":"https://openalex.org/W4392255466","doi":"https://doi.org/10.1145/3637732.3637780"},"language":"en","primary_location":{"id":"doi:10.1145/3637732.3637780","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637732.3637780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"},"type":"article","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/A5080873978","display_name":"Xuemin Zhao","orcid":"https://orcid.org/0000-0003-4103-4533"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuemin Zhao","raw_affiliation_strings":["Yunnan University, China"],"raw_orcid":"https://orcid.org/0000-0003-4103-4533","affiliations":[{"raw_affiliation_string":"Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111764319","display_name":"R.-Y. Duan","orcid":"https://orcid.org/0009-0004-4581-2317"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Duan","raw_affiliation_strings":["Yunnan University, China"],"raw_orcid":"https://orcid.org/0009-0004-4581-2317","affiliations":[{"raw_affiliation_string":"Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000436275","display_name":"Shaowen Yao","orcid":"https://orcid.org/0000-0003-1516-4246"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowen Yao","raw_affiliation_strings":["Yunnan University, China"],"raw_orcid":"https://orcid.org/0000-0003-1516-4246","affiliations":[{"raw_affiliation_string":"Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080873978"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.1499,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6102171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"80","last_page":"85"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.9994999766349792,"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/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.9994999766349792,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9954000115394592,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9926000237464905,"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/chromatin","display_name":"Chromatin","score":0.6720725893974304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6485600471496582},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6384096145629883},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.631837010383606},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6198452711105347},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5002713203430176},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4642665386199951},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4518831968307495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4368836283683777},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.41468843817710876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39512917399406433},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3924587070941925},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3002087473869324},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.14979013800621033},{"id":"https://openalex.org/keywords/dna","display_name":"DNA","score":0.13988420367240906},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13251984119415283},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11062949895858765},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.08052492141723633}],"concepts":[{"id":"https://openalex.org/C83640560","wikidata":"https://www.wikidata.org/wiki/Q180951","display_name":"Chromatin","level":3,"score":0.6720725893974304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6485600471496582},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6384096145629883},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.631837010383606},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6198452711105347},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5002713203430176},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4642665386199951},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4518831968307495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4368836283683777},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.41468843817710876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39512917399406433},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3924587070941925},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3002087473869324},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.14979013800621033},{"id":"https://openalex.org/C552990157","wikidata":"https://www.wikidata.org/wiki/Q7430","display_name":"DNA","level":2,"score":0.13988420367240906},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13251984119415283},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11062949895858765},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.08052492141723633},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637732.3637780","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637732.3637780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1973062929","https://openalex.org/W1987971958","https://openalex.org/W2036887984","https://openalex.org/W2070021921","https://openalex.org/W2097798909","https://openalex.org/W2117977423","https://openalex.org/W2133665775","https://openalex.org/W2163412235","https://openalex.org/W2507209892","https://openalex.org/W2803256172","https://openalex.org/W2964121744","https://openalex.org/W3007609047","https://openalex.org/W3035022492","https://openalex.org/W3094502228","https://openalex.org/W3171125843","https://openalex.org/W3180355996","https://openalex.org/W6959643953"],"related_works":["https://openalex.org/W4286930115","https://openalex.org/W2368824897","https://openalex.org/W1508050556","https://openalex.org/W1910862367","https://openalex.org/W2379365082","https://openalex.org/W2370747590","https://openalex.org/W2030109976","https://openalex.org/W2369260257","https://openalex.org/W2389120450","https://openalex.org/W55249799"],"abstract_inverted_index":{"The":[0,56],"spatial":[1],"arrangement":[2,107],"revealed":[3],"by":[4,51,86,104],"chromatin":[5,72,97],"interactions":[6,73],"in":[7],"Hi-C":[8,18,49,76,130],"data":[9,20,50,143],"is":[10],"inherently":[11],"dependent":[12],"on":[13],"its":[14],"resolution.":[15],"Obtaining":[16],"high-resolution":[17],"sequencing":[19,36],"remains":[21],"a":[22,83,141],"significant":[23],"challenge":[24],"for":[25,44],"many":[26],"cell":[27],"lines":[28],"due":[29],"to":[30,65,139],"the":[31,46,53,60,67,80,88,100,105,109,129],"prohibitive":[32],"costs":[33],"of":[34,48,108],"increasing":[35],"depth.":[37],"This":[38],"study":[39],"presents":[40],"an":[41],"innovative":[42],"method":[43,58,81,121],"improving":[45],"resolution":[47],"exploiting":[52],"Transformer":[54],"model.":[55],"proposed":[57],"leverages":[59],"Transformer's":[61],"inherent":[62],"attention":[63],"mechanism":[64],"capture":[66],"intricate":[68],"interplay":[69],"between":[70,90],"global":[71],"within":[74],"low-resolution":[75],"matrices.":[77],"In":[78],"addition,":[79],"takes":[82],"comprehensive":[84],"view":[85],"considering":[87],"interrelationship":[89],"local":[91],"attributes":[92],"that":[93],"characterize":[94],"smaller":[95],"three-dimensional":[96,106],"structures":[98],"and":[99,133,137],"overarching":[101],"context":[102],"provided":[103],"larger":[110],"matrix.":[111],"Significantly":[112],"different":[113],"from":[114],"previous":[115],"methods":[116],"involving":[117],"image":[118],"segmentation,":[119,127],"our":[120],"does":[122],"not":[123],"use":[124],"with":[125],"matrix":[126,131],"encodes":[128],"directly,":[132],"uses":[134],"model-based":[135],"encoding":[136],"decoding":[138],"achieve":[140],"refined":[142],"representation.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}