{"id":"https://openalex.org/W4293518013","doi":"https://doi.org/10.1109/cibcb55180.2022.9863058","title":"SetQuence & SetOmic: Deep Set Transformer-based Representations of Cancer Multi-Omics","display_name":"SetQuence & SetOmic: Deep Set Transformer-based Representations of Cancer Multi-Omics","publication_year":2022,"publication_date":"2022-08-15","ids":{"openalex":"https://openalex.org/W4293518013","doi":"https://doi.org/10.1109/cibcb55180.2022.9863058"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb55180.2022.9863058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb55180.2022.9863058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","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/A5035708927","display_name":"Neringa Jurenaite","orcid":"https://orcid.org/0000-0002-3959-7452"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Neringa Jurenaite","raw_affiliation_strings":["Technische Universität Dresden,ZIH,Dresden,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität Dresden,ZIH,Dresden,Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088413936","display_name":"Daniel Le\u00f3n-Peri\u00f1\u00e1n","orcid":"https://orcid.org/0000-0002-7970-0362"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Le\u00f3n-Peri\u00f1\u00e1n","raw_affiliation_strings":["Technische Universität Dresden,ZIH,Dresden,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität Dresden,ZIH,Dresden,Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078328009","display_name":"Veronika Donath","orcid":null},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Veronika Donath","raw_affiliation_strings":["Technische Universität Dresden,ZIH,Dresden,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität Dresden,ZIH,Dresden,Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078560306","display_name":"Sunna Torge","orcid":"https://orcid.org/0000-0001-9756-6390"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sunna Torge","raw_affiliation_strings":["Technische Universität Dresden,ZIH,Dresden,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität Dresden,ZIH,Dresden,Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017416649","display_name":"Ren\u00e9 J\u00e4kel","orcid":"https://orcid.org/0000-0001-6260-5222"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ren\u00e9 J\u00e4kel","raw_affiliation_strings":["Technische Universität Dresden,ZIH,Dresden,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität Dresden,ZIH,Dresden,Germany","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035708927"],"corresponding_institution_ids":["https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":0.3431,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55243369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9987000226974487,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9987000226974487,"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":0.9968000054359436,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6712911128997803},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.651177704334259},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6252796649932861},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6186004281044006},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5599960684776306},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4965525269508362},{"id":"https://openalex.org/keywords/genomics","display_name":"Genomics","score":0.41327643394470215},{"id":"https://openalex.org/keywords/genome","display_name":"Genome","score":0.3846886456012726},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.16658639907836914},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.12057021260261536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6712911128997803},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.651177704334259},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6252796649932861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6186004281044006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5599960684776306},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4965525269508362},{"id":"https://openalex.org/C189206191","wikidata":"https://www.wikidata.org/wiki/Q222046","display_name":"Genomics","level":4,"score":0.41327643394470215},{"id":"https://openalex.org/C141231307","wikidata":"https://www.wikidata.org/wiki/Q7020","display_name":"Genome","level":3,"score":0.3846886456012726},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.16658639907836914},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.12057021260261536},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb55180.2022.9863058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb55180.2022.9863058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1868978502","https://openalex.org/W1949372270","https://openalex.org/W2000415243","https://openalex.org/W2005895632","https://openalex.org/W2048383496","https://openalex.org/W2053976130","https://openalex.org/W2085181566","https://openalex.org/W2114416030","https://openalex.org/W2124954099","https://openalex.org/W2133107935","https://openalex.org/W2142646761","https://openalex.org/W2157193683","https://openalex.org/W2158485828","https://openalex.org/W2163350781","https://openalex.org/W2441845901","https://openalex.org/W2474747771","https://openalex.org/W2519564115","https://openalex.org/W2561675875","https://openalex.org/W2564018391","https://openalex.org/W2567947578","https://openalex.org/W2588118089","https://openalex.org/W2610332124","https://openalex.org/W2611138580","https://openalex.org/W2612690371","https://openalex.org/W2790881798","https://openalex.org/W2800388620","https://openalex.org/W2891796218","https://openalex.org/W2896457183","https://openalex.org/W2898455197","https://openalex.org/W2937762029","https://openalex.org/W2955502047","https://openalex.org/W2955621471","https://openalex.org/W2958089299","https://openalex.org/W2964110616","https://openalex.org/W2977711279","https://openalex.org/W2996227376","https://openalex.org/W3004060585","https://openalex.org/W3005948817","https://openalex.org/W3025589456","https://openalex.org/W3034518255","https://openalex.org/W3096948214","https://openalex.org/W3115495889","https://openalex.org/W3127238141","https://openalex.org/W3129199640","https://openalex.org/W3164535579","https://openalex.org/W3164907662","https://openalex.org/W3173875945","https://openalex.org/W3176966473","https://openalex.org/W3180571536","https://openalex.org/W3195201018","https://openalex.org/W3195529769","https://openalex.org/W3212249145","https://openalex.org/W4223476561","https://openalex.org/W4231031051","https://openalex.org/W4283815817","https://openalex.org/W4287724045","https://openalex.org/W4288311604","https://openalex.org/W4288316086","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6679434410","https://openalex.org/W6679659327","https://openalex.org/W6685133223","https://openalex.org/W6731272478","https://openalex.org/W6734194636","https://openalex.org/W6736518430","https://openalex.org/W6737947904","https://openalex.org/W6739633048","https://openalex.org/W6755207826","https://openalex.org/W6764313071","https://openalex.org/W6766350953","https://openalex.org/W6804003978","https://openalex.org/W6810332151"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2770593030","https://openalex.org/W2611989081","https://openalex.org/W3154990682","https://openalex.org/W2560201613","https://openalex.org/W2086525401","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W4312219546","https://openalex.org/W4230611425"],"abstract_inverted_index":{"In":[0],"oncology,":[1],"Deep":[2,68],"Learning":[3],"has":[4],"shown":[5,125],"great":[6],"potential":[7],"to":[8,36,77,107,126,129,149],"personalise":[9],"tasks":[10,64],"such":[11,26,139],"as":[12,81,83,140],"tumour":[13],"type":[14],"classification,":[15],"based":[16],"on":[17,48],"per-patient":[18],"omics":[19,87],"data-sets.":[20],"Being":[21],"high":[22],"dimensional,":[23],"incorporation":[24],"of":[25,51,62,86,117,134],"data":[27,88],"in":[28,89,137,152],"one":[29],"model":[30,76],"is":[31],"a":[32,90],"challenge,":[33],"often":[34],"leading":[35],"one-dimensional":[37],"studies":[38],"and,":[39],"therefore,":[40],"information":[41,104],"loss.":[42],"Instead,":[43],"we":[44,73],"first":[45],"propose":[46],"relying":[47],"non-fixed":[49],"sets":[50],"mutated":[52],"genome":[53],"sequences,":[54],"which":[55],"can":[56],"be":[57,127],"used":[58],"for":[59],"supervised":[60],"learning":[61],"oncology-relevant":[63],"by":[65],"our":[66,122],"Transformer-based":[67],"Neural":[69],"Network,":[70],"SETQUENCE.":[71],"Second,":[72],"extend":[74],"the":[75,131,147],"incorporate":[78],"these":[79,97],"representations":[80],"well":[82],"multiple":[84],"sources":[85],"flexible":[91],"way":[92],"with":[93],"SETOMIC.":[94],"Evaluation,":[95],"using":[96],"representations,":[98],"shows":[99],"improved":[100],"robustness":[101],"and":[102,157],"reduced":[103],"loss":[105],"compared":[106],"previous":[108],"approaches,":[109],"while":[110],"still":[111],"being":[112],"computationally":[113],"tractable.":[114],"By":[115],"means":[116],"Explainable":[118],"Artificial":[119],"Intelligence":[120],"methods,":[121],"models":[123],"are":[124],"able":[128],"recapitulate":[130],"biological":[132],"contribution":[133],"several":[135],"features":[136],"cancer,":[138],"individual":[141],"expression":[142],"loci.":[143],"This":[144],"validation":[145],"opens":[146],"door":[148],"novel":[150],"directions":[151],"multi-faceted":[153],"genome-wide":[154],"biomarker":[155],"discovery":[156],"personalised":[158],"treatment":[159],"among":[160],"other":[161],"presently":[162],"clinically":[163],"relevant":[164],"tasks.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}