{"id":"https://openalex.org/W4409659776","doi":"https://doi.org/10.1109/tcbbio.2025.3563354","title":"A Deep Learning Framework for Chromatin Loop De Novo Prediction With Enhanced Feature Extraction","display_name":"A Deep Learning Framework for Chromatin Loop De Novo Prediction With Enhanced Feature Extraction","publication_year":2025,"publication_date":"2025-04-22","ids":{"openalex":"https://openalex.org/W4409659776","doi":"https://doi.org/10.1109/tcbbio.2025.3563354","pmid":"https://pubmed.ncbi.nlm.nih.gov/40811287"},"language":"en","primary_location":{"id":"doi:10.1109/tcbbio.2025.3563354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3563354","pdf_url":null,"source":{"id":"https://openalex.org/S5407042751","display_name":"IEEE Transactions on Computational Biology and Bioinformatics","issn_l":"2998-4165","issn":["2998-4165"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101920535","display_name":"Jialiang Sun","orcid":"https://orcid.org/0000-0003-1898-9593"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jialiang Sun","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China","Software College of Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Software College of Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414608","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0001-5516-0157"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Liu","raw_affiliation_strings":["Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin, China","College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101920535"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07346607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"6","first_page":"2387","last_page":"2397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.96670001745224,"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":0.96670001745224,"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":0.6200863718986511},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.5974457263946533},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5815896987915039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5498785376548767},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5335225462913513},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5293835997581482},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.47552064061164856},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44435709714889526},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.4176047444343567},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35955166816711426},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.26406991481781006},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.24091112613677979},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1568930745124817},{"id":"https://openalex.org/keywords/dna","display_name":"DNA","score":0.15598687529563904},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.13961273431777954},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.1331779658794403}],"concepts":[{"id":"https://openalex.org/C83640560","wikidata":"https://www.wikidata.org/wiki/Q180951","display_name":"Chromatin","level":3,"score":0.6200863718986511},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.5974457263946533},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5815896987915039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5498785376548767},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5335225462913513},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5293835997581482},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.47552064061164856},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44435709714889526},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4176047444343567},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35955166816711426},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.26406991481781006},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.24091112613677979},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1568930745124817},{"id":"https://openalex.org/C552990157","wikidata":"https://www.wikidata.org/wiki/Q7430","display_name":"DNA","level":2,"score":0.15598687529563904},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.13961273431777954},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.1331779658794403},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D002843","descriptor_name":"Chromatin","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D020014","descriptor_name":"K562 Cells","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020014","descriptor_name":"K562 Cells","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020014","descriptor_name":"K562 Cells","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcbbio.2025.3563354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3563354","pdf_url":null,"source":{"id":"https://openalex.org/S5407042751","display_name":"IEEE Transactions on Computational Biology and Bioinformatics","issn_l":"2998-4165","issn":["2998-4165"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},{"id":"pmid:40811287","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40811287","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":"IEEE transactions on computational biology and bioinformatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6485093558","display_name":null,"funder_award_id":"23JCYBJC01740","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G8644249901","display_name":null,"funder_award_id":"62272246","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1973062929","https://openalex.org/W2092390808","https://openalex.org/W2096192437","https://openalex.org/W2129795133","https://openalex.org/W2140952049","https://openalex.org/W2167852161","https://openalex.org/W2169710039","https://openalex.org/W2195190137","https://openalex.org/W2250539671","https://openalex.org/W2519241029","https://openalex.org/W2770178180","https://openalex.org/W2781657900","https://openalex.org/W2792734199","https://openalex.org/W2980926019","https://openalex.org/W2988126442","https://openalex.org/W3108406690","https://openalex.org/W3109356327","https://openalex.org/W4205134693","https://openalex.org/W4282921441","https://openalex.org/W4295907576","https://openalex.org/W4310594072","https://openalex.org/W4311588897","https://openalex.org/W4400519906","https://openalex.org/W4404035652"],"related_works":["https://openalex.org/W4286930115","https://openalex.org/W24774503","https://openalex.org/W3004891660","https://openalex.org/W2969540308","https://openalex.org/W2414971881","https://openalex.org/W4206381471","https://openalex.org/W1886874180","https://openalex.org/W42421305","https://openalex.org/W2400987468","https://openalex.org/W1598419885"],"abstract_inverted_index":{"Chromatin":[0],"encompasses":[1],"a":[2,17,54,76,109],"variety":[3],"of":[4,27,33,37,56,85,99,158],"three-dimensional":[5],"structures":[6],"with":[7,70,92,150],"distinct":[8],"forms":[9],"and":[10,24,51,73,83,107,161],"ranges,":[11],"among":[12,47,103],"which":[13],"chromatin":[14,38,86,116,153],"loops":[15],"play":[16],"crucial":[18],"role":[19,36],"in":[20,127],"gene":[21],"regulatory":[22],"mechanisms":[23],"the":[25,31,34,45,101,143,156],"maintenance":[26],"cellular":[28],"homeostasis.":[29],"Despite":[30],"recognition":[32],"critical":[35],"loops,":[39,154],"existing":[40,124],"prediction":[41,58,69,82,140],"models":[42],"often":[43],"overlook":[44],"heterogeneity":[46],"different":[48],"feature":[49,105,131],"data,":[50],"there":[52],"is":[53],"scarcity":[55],"corresponding":[57],"tools.":[59],"To":[60],"fill":[61],"this":[62],"gap,":[63],"we":[64],"introduce":[65],"CHASOS2":[66,88,122,137],"(CHromatin":[67],"loop":[68],"Anchor":[71],"Score":[72],"OCR":[74],"Score),":[75],"user-friendly":[77],"toolkit":[78,141],"for":[79],"de":[80,138],"novo":[81,139],"evaluation":[84],"loop.":[87],"uses":[89],"convolutional":[90],"modules":[91],"multi-receptive":[93],"fields":[94],"to":[95,114],"generate":[96],"features":[97],"capable":[98],"mitigating":[100],"heterogeneities":[102],"diverse":[104],"data":[106],"employs":[108],"gradient":[110],"boosting":[111],"tree":[112],"model":[113],"predict":[115],"loops.":[117],"Experimental":[118],"evaluations":[119],"indicate":[120],"that":[121],"outperforms":[123],"methods,":[125],"particularly":[126],"scenarios":[128],"involving":[129],"heterogeneous":[130],"data.":[132],"A":[133],"case":[134],"study":[135],"applying":[136],"on":[142],"K562":[144],"cell":[145],"line":[146],"demonstrates":[147],"high":[148],"consistency":[149],"ChIA-PET":[151],"identified":[152],"validating":[155],"effectiveness":[157],"our":[159],"method":[160],"toolkit.":[162]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}