{"id":"https://openalex.org/W4385695838","doi":"https://doi.org/10.1145/3586139.3586140","title":"Predicting single cell genotypes from single cell expression profiles in AML using deep learning","display_name":"Predicting single cell genotypes from single cell expression profiles in AML using deep learning","publication_year":2023,"publication_date":"2023-01-13","ids":{"openalex":"https://openalex.org/W4385695838","doi":"https://doi.org/10.1145/3586139.3586140"},"language":"en","primary_location":{"id":"doi:10.1145/3586139.3586140","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3586139.3586140","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3586139.3586140","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Conference on Bioscience Biochemistry and Bioinformatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3586139.3586140","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014475135","display_name":"Georgios Asimomitis","orcid":"https://orcid.org/0000-0002-9479-5451"},"institutions":[{"id":"https://openalex.org/I1334819555","display_name":"Memorial Sloan Kettering Cancer Center","ror":"https://ror.org/02yrq0923","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1334819555"]},{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR","US"],"is_corresponding":true,"raw_author_name":"Georgios Asimomitis","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA and \rBiomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9479-5451","affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA and \rBiomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059","https://openalex.org/I1334819555"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091640945","display_name":"Maria Sirenko","orcid":"https://orcid.org/0000-0001-7816-8071"},"institutions":[{"id":"https://openalex.org/I1334819555","display_name":"Memorial Sloan Kettering Cancer Center","ror":"https://ror.org/02yrq0923","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1334819555"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maria Sirenko","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA"],"raw_orcid":"https://orcid.org/0000-0001-7816-8071","affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA","institution_ids":["https://openalex.org/I1334819555"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005458506","display_name":"Christos Fotis","orcid":"https://orcid.org/0000-0002-2074-1127"},"institutions":[{"id":"https://openalex.org/I203474044","display_name":"National Centre of Scientific Research \"Demokritos\"","ror":"https://ror.org/038jp4m40","country_code":"GR","type":"facility","lineage":["https://openalex.org/I203474044"]},{"id":"https://openalex.org/I4210118840","display_name":"Science and Technology Park of Crete","ror":"https://ror.org/02ddqp560","country_code":"GR","type":"other","lineage":["https://openalex.org/I4210118840"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Christos Fotis","raw_affiliation_strings":["ProtATonce Ltd, Demokritos Science Park, Greece"],"raw_orcid":"https://orcid.org/0000-0002-2074-1127","affiliations":[{"raw_affiliation_string":"ProtATonce Ltd, Demokritos Science Park, Greece","institution_ids":["https://openalex.org/I4210118840","https://openalex.org/I203474044"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086217179","display_name":"Dan A. Landau","orcid":"https://orcid.org/0000-0003-2346-9541"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4387153466","display_name":"Weill Cornell Medicine","ror":"https://ror.org/02r109517","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan A Landau","raw_affiliation_strings":["Meyer Cancer Center, Weill Cornell Medicine, USA"],"raw_orcid":"https://orcid.org/0000-0003-2346-9541","affiliations":[{"raw_affiliation_string":"Meyer Cancer Center, Weill Cornell Medicine, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4387153466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053848151","display_name":"Leonidas G. Alexopoulos","orcid":"https://orcid.org/0000-0003-0425-166X"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Leonidas G Alexopoulos","raw_affiliation_strings":["Biomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0003-0425-166X","affiliations":[{"raw_affiliation_string":"Biomedical Systems Laboratory, Department of Mechanical Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077331342","display_name":"Elli Papaemmanuil","orcid":"https://orcid.org/0000-0003-1709-8983"},"institutions":[{"id":"https://openalex.org/I1334819555","display_name":"Memorial Sloan Kettering Cancer Center","ror":"https://ror.org/02yrq0923","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1334819555"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elli Papaemmanuil","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA"],"raw_orcid":"https://orcid.org/0000-0003-1709-8983","affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, USA","institution_ids":["https://openalex.org/I1334819555"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5014475135"],"corresponding_institution_ids":["https://openalex.org/I1334819555","https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.2999,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63445886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9995999932289124,"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":0.9995999932289124,"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/T10309","display_name":"Acute Myeloid Leukemia Research","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2720","display_name":"Hematology"},"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/T11287","display_name":"Cancer Genomics and Diagnostics","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/deep-learning","display_name":"Deep learning","score":0.6514899730682373},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.6055305004119873},{"id":"https://openalex.org/keywords/cell","display_name":"Cell","score":0.4789896011352539},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.47155997157096863},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.4467521011829376},{"id":"https://openalex.org/keywords/genotype","display_name":"Genotype","score":0.4449990689754486},{"id":"https://openalex.org/keywords/cell-type","display_name":"Cell type","score":0.4411521553993225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43084341287612915},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.4104096293449402},{"id":"https://openalex.org/keywords/myeloid-leukemia","display_name":"Myeloid leukemia","score":0.4103332459926605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37336695194244385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3570699691772461},{"id":"https://openalex.org/keywords/cancer-research","display_name":"Cancer research","score":0.31579428911209106},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.27495211362838745}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6514899730682373},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.6055305004119873},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.4789896011352539},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.47155997157096863},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.4467521011829376},{"id":"https://openalex.org/C135763542","wikidata":"https://www.wikidata.org/wiki/Q106016","display_name":"Genotype","level":3,"score":0.4449990689754486},{"id":"https://openalex.org/C189014844","wikidata":"https://www.wikidata.org/wiki/Q189118","display_name":"Cell type","level":3,"score":0.4411521553993225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43084341287612915},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.4104096293449402},{"id":"https://openalex.org/C2778729363","wikidata":"https://www.wikidata.org/wiki/Q11688946","display_name":"Myeloid leukemia","level":2,"score":0.4103332459926605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37336695194244385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3570699691772461},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.31579428911209106},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.27495211362838745}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3586139.3586140","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3586139.3586140","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3586139.3586140","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Conference on Bioscience Biochemistry and Bioinformatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3586139.3586140","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3586139.3586140","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3586139.3586140","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Conference on Bioscience Biochemistry and Bioinformatics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G1350487908","display_name":null,"funder_award_id":"F31 CA 254130","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385695838.pdf","grobid_xml":"https://content.openalex.org/works/W4385695838.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1660133344","https://openalex.org/W1973095183","https://openalex.org/W2035474025","https://openalex.org/W2109272381","https://openalex.org/W2112998845","https://openalex.org/W2153010521","https://openalex.org/W2339658711","https://openalex.org/W2419140434","https://openalex.org/W2559537906","https://openalex.org/W2565020911","https://openalex.org/W2784595248","https://openalex.org/W2800392236","https://openalex.org/W2916458303","https://openalex.org/W2949177718","https://openalex.org/W2951506174","https://openalex.org/W2954384525","https://openalex.org/W2963847595","https://openalex.org/W2968098426","https://openalex.org/W2978541146","https://openalex.org/W2997280954","https://openalex.org/W3039031205","https://openalex.org/W3085380432","https://openalex.org/W3092632847","https://openalex.org/W3138479716","https://openalex.org/W3145969289","https://openalex.org/W3175769723","https://openalex.org/W4210802543","https://openalex.org/W4226238799","https://openalex.org/W6929269793"],"related_works":["https://openalex.org/W2134373856","https://openalex.org/W4375867731","https://openalex.org/W2385665726","https://openalex.org/W2347271704","https://openalex.org/W2391157579","https://openalex.org/W3029453589","https://openalex.org/W2325793530","https://openalex.org/W2036624756","https://openalex.org/W2372977423","https://openalex.org/W4392817421"],"abstract_inverted_index":{"Acute":[0],"myeloid":[1],"leukemia":[2],"(AML)":[3],"is":[4],"an":[5,148],"aggressive":[6],"hematologic":[7],"malignancy":[8],"composed":[9],"of":[10,13,27,42,73,111,150,162,182,206,228],"a":[11,81,116,158],"mixture":[12],"genotypically,":[14],"phenotypically":[15],"and":[16,34,118,134,180,191,216],"functionally":[17],"diverse":[18],"cell":[19,31,64,126,208,213],"populations":[20],"including":[21],"wild-type":[22,102],"(WT)":[23,103],"cells.":[24],"The":[25],"generation":[26],"high":[28],"throughput":[29],"single":[30,63,125,207,212],"gene":[32,65],"expression":[33,66,214],"mutational":[35,109],"profiles":[36,210],"in":[37,115,177,185],"AML":[38,132],"enables":[39],"the":[40,59,62,70,77,98,108,139,143,153,171,189,204,219,226],"deployment":[41],"deep":[43,93,200],"learning":[44,94,201],"frameworks":[45],"for":[46,203,225],"gaining":[47],"insights":[48],"on":[49,124,170],"how":[50,218],"genotypic":[51,209],"changes":[52],"are":[53],"associated":[54],"with":[55,69],"disease":[56],"phenotypes.":[57],"However,":[58],"question":[60],"if":[61],"patterns":[67],"together":[68],"computational":[71],"power":[72],"neural":[74],"networks":[75,173],"have":[76],"capacity":[78],"to":[79,96],"predict":[80,97],"cell's":[82,99],"genotype":[83],"remains":[84],"unclear.":[85],"In":[86,138],"this":[87,196],"study,":[88],"we":[89],"train":[90],"two":[91,199],"supervised":[92],"models":[95,221],"malignant":[100],"or":[101],"status":[104,110],"as":[105,107,188],"well":[106],"specific":[112],"genomic":[113],"abnormalities":[114],"binary":[117,144],"multi-class":[119,154],"multi-label":[120,155],"setting":[121],"respectively,":[122],"based":[123],"RNA":[127],"sequencing":[128],"data":[129,215],"from":[130,211],"6":[131],"patients":[133],"4":[135],"healthy":[136],"individuals.":[137],"independent":[140],"test":[141],"sets,":[142],"classification":[145],"model":[146,156],"achieved":[147,157],"accuracy":[149],"98%":[151],"while":[152],"macro-average":[159],"AUC":[160],"ROC":[161],"0.84.":[163],"Moreover,":[164],"applying":[165],"black":[166],"box":[167],"feature":[168],"selection":[169],"trained":[172,220],"identified":[174],"genes":[175],"involved":[176],"biological":[178],"processes":[179],"pathways":[181],"reported":[183],"significance":[184],"AML,":[186],"such":[187],"IL-2/STAT5":[190],"NF-kB":[192],"signaling":[193],"pathways.":[194],"Overall,":[195],"study":[197],"proposes":[198],"tasks":[202],"prediction":[205],"showcases":[217],"can":[222],"be":[223],"used":[224],"derivation":[227],"biologically":[229],"related":[230],"signals.":[231]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
