{"id":"https://openalex.org/W4406949430","doi":"https://doi.org/10.1109/tcbbio.2025.3536282","title":"A ML Framework for Genetic Sequence Identification Using 2D Electrical Conductance Probability Distributions from Mixed Data Sets","display_name":"A ML Framework for Genetic Sequence Identification Using 2D Electrical Conductance Probability Distributions from Mixed Data Sets","publication_year":2025,"publication_date":"2025-01-29","ids":{"openalex":"https://openalex.org/W4406949430","doi":"https://doi.org/10.1109/tcbbio.2025.3536282","pmid":"https://pubmed.ncbi.nlm.nih.gov/40811404"},"language":"en","primary_location":{"id":"doi:10.1109/tcbbio.2025.3536282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3536282","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/A5100723440","display_name":"Yiren Wang","orcid":"https://orcid.org/0000-0003-1102-4609"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiren Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085094109","display_name":"Hongning Wang","orcid":"https://orcid.org/0000-0002-6524-9195"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongning Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052769337","display_name":"Arindam K. Das","orcid":"https://orcid.org/0000-0001-6605-2258"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam K. Das","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016460436","display_name":"M. P. Anantram","orcid":"https://orcid.org/0000-0003-2539-7457"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. P. Anantram","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100723440"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01638821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"2","first_page":"790","last_page":"799"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9713000059127808,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9713000059127808,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9325000047683716,"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/identification","display_name":"Identification (biology)","score":0.6829135417938232},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.634531557559967},{"id":"https://openalex.org/keywords/conductance","display_name":"Conductance","score":0.6148272752761841},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.39883989095687866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38170990347862244},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.3814096748828888},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3195330500602722},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.15042424201965332},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.14388737082481384},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1226082444190979}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6829135417938232},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.634531557559967},{"id":"https://openalex.org/C121932024","wikidata":"https://www.wikidata.org/wiki/Q5159376","display_name":"Conductance","level":2,"score":0.6148272752761841},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39883989095687866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38170990347862244},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3814096748828888},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3195330500602722},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.15042424201965332},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.14388737082481384},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1226082444190979},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcbbio.2025.3536282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbbio.2025.3536282","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:40811404","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40811404","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/G4981664799","display_name":null,"funder_award_id":"FMRG 2328217","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7149835473","display_name":null,"funder_award_id":"FuSe-TG 2235294","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7815925309","display_name":null,"funder_award_id":"GCR 2317843","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1980969344","https://openalex.org/W2004818804","https://openalex.org/W2005184097","https://openalex.org/W2026523107","https://openalex.org/W2026625428","https://openalex.org/W2044433401","https://openalex.org/W2606684276","https://openalex.org/W2895835607","https://openalex.org/W2898654087","https://openalex.org/W2922512504","https://openalex.org/W3014828600","https://openalex.org/W3016715069","https://openalex.org/W3018736469","https://openalex.org/W3114541054","https://openalex.org/W3186857781","https://openalex.org/W3197449635","https://openalex.org/W3199067426","https://openalex.org/W4321235141","https://openalex.org/W4323975082","https://openalex.org/W4367176505","https://openalex.org/W4368275167","https://openalex.org/W4386102936","https://openalex.org/W4398212192","https://openalex.org/W6631190155","https://openalex.org/W6797962120","https://openalex.org/W6810188501","https://openalex.org/W6842860981"],"related_works":["https://openalex.org/W2035271760","https://openalex.org/W2144661048","https://openalex.org/W166353894","https://openalex.org/W2030970284","https://openalex.org/W2061523378","https://openalex.org/W2124181728","https://openalex.org/W1994253593","https://openalex.org/W2067124413","https://openalex.org/W2132501977","https://openalex.org/W4353113454"],"abstract_inverted_index":{"Genetic":[0],"sequence":[1,51],"identification":[2,193],"from":[3,52,121],"electrical":[4,19],"characterization":[5],"of":[6,31,154,162,171,177],"single":[7,22,54,182],"molecules":[8,23],"has":[9],"emerged":[10],"as":[11,102],"a":[12,50,68],"promising":[13],"alternative":[14],"to":[15,28,48,117,134,190],"traditional":[16],"approaches.":[17],"Since":[18],"data":[20,176],"on":[21,66,195],"is":[24,39,174,187],"extremely":[25],"noisy":[26],"due":[27],"the":[29,43,109,169],"limitations":[30],"even":[32],"state-of-the-art":[33],"approaches,":[34],"achieving":[35],"high":[36],"detection":[37],"rates":[38],"challenging,":[40],"particularly":[41],"when":[42],"task":[44],"involves":[45],"being":[46],"able":[47],"distinguish":[49],"its":[53],"base-pair":[55,183],"mismatches.":[56],"To":[57],"address":[58],"this":[59],"issue,":[60],"we":[61],"propose":[62],"an":[63,73,158],"architecture":[64],"based":[65,194],"combining":[67],"convolutional":[69],"neural":[70],"network":[71],"with":[72,104,113,132],"ensemble":[74],"learning":[75],"method,":[76],"XGBoost.":[77],"In":[78],"addition,":[79],"four":[80],"different":[81],"input":[82],"feature":[83,118],"representations":[84],"are":[85,130,142],"considered,":[86],"1D":[87],"conductance":[88,93,139,175],"probability":[89,96,128,140],"distributions":[90,97,129,141],"and":[91,146,180],"2D":[92,127],"versus":[94],"distance":[95],"which":[98],"can":[99],"be":[100],"viewed":[101],"images,":[103],"or":[105],"without":[106],"averaging":[107,114],"over":[108],"experimental":[110],"parameters.":[111],"The":[112],"case":[115],"corresponds":[116],"matrices":[119],"derived":[120],"mixed":[122],"datasets.":[123],"We":[124],"find":[125],"that":[126],"helpful":[131],"respect":[133],"classifier":[135],"accuracy,":[136],"but":[137],"averaged":[138],"much":[143],"more":[144],"impactful":[145],"significantly":[147],"enhance":[148],"prediction":[149],"accuracy.":[150],"Our":[151],"quantitative":[152],"analysis":[153,173],"multiple":[155],"sequences":[156],"shows":[157],"impressive":[159],"performance":[160],"increase":[161],"approximately":[163],"10%":[164],"for":[165],"all":[166],"sequences.":[167],"While":[168],"basis":[170],"our":[172,185],"DNA":[178],"strands":[179],"their":[181,196],"mismatches,":[184],"method":[186],"generally":[188],"applicable":[189],"other":[191],"single-molecule":[192],"conductance.":[197]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}