{"id":"https://openalex.org/W3101266628","doi":"https://doi.org/10.1145/3388440.3414215","title":"Avocado","display_name":"Avocado","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3101266628","doi":"https://doi.org/10.1145/3388440.3414215","mag":"3101266628"},"language":"en","primary_location":{"id":"doi:10.1145/3388440.3414215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3414215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","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/A5081318122","display_name":"Jacob Schreiber","orcid":"https://orcid.org/0000-0003-4230-6625"},"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":"Jacob Schreiber","raw_affiliation_strings":["Genome Science, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Genome Science, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087986958","display_name":"Timothy Durham","orcid":"https://orcid.org/0000-0003-2056-4199"},"institutions":[{"id":"https://openalex.org/I4210091697","display_name":"Hospitality Homes","ror":"https://ror.org/00h2d8k73","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210091697"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Durham","raw_affiliation_strings":["HHMI, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"HHMI, Boston, MA, USA","institution_ids":["https://openalex.org/I4210091697"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057375933","display_name":"William Stafford Noble","orcid":"https://orcid.org/0000-0001-7283-4715"},"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":"William Noble","raw_affiliation_strings":["Genome Science, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Genome Science, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091674429","display_name":"Jeffrey A. Bilmes","orcid":"https://orcid.org/0000-0002-7372-8778"},"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":"Jeffrey Bilmes","raw_affiliation_strings":["Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical 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/A5081318122"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.2299,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70258662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12571","display_name":"Soybean genetics and cultivation","score":0.9294000267982483,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12571","display_name":"Soybean genetics and cultivation","score":0.9294000267982483,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9068999886512756,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7994952201843262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7432093024253845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5455701351165771},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5093291997909546},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4957631528377533},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4728562831878662},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4535166323184967},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43156009912490845},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.43039727210998535},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07685586810112}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7994952201843262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7432093024253845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5455701351165771},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5093291997909546},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4957631528377533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4728562831878662},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4535166323184967},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43156009912490845},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.43039727210998535},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07685586810112},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3388440.3414215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3414215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2071158428","display_name":null,"funder_award_id":"U54 DK107979","funder_id":"https://openalex.org/F4320337373","funder_display_name":"Center for Information Technology"}],"funders":[{"id":"https://openalex.org/F4320337373","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2914170472","https://openalex.org/W3013674494","https://openalex.org/W3101266628"],"related_works":["https://openalex.org/W2032233321","https://openalex.org/W3121970507","https://openalex.org/W2110028391","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"In":[0,56],"the":[1,4,24,38,100,138],"past":[2],"decade,":[3],"use":[5],"of":[6,17,37,60,66,102,104,106,122],"high-throughput":[7],"sequencing":[8],"assays":[9],"has":[10],"allowed":[11],"researchers":[12],"to":[13,50,95],"experimentally":[14],"acquire":[15],"thousands":[16,105],"functional":[18,107,139],"measurements":[19,31,81],"for":[20],"each":[21],"basepair":[22],"in":[23],"human":[25],"genome.":[26],"Despite":[27],"their":[28],"value,":[29],"these":[30,67,80,89,130],"are":[32],"only":[33],"a":[34,57,70,120],"small":[35],"fraction":[36],"potential":[39],"experiments":[40,108],"that":[41,78,88,109,128],"could":[42],"be":[43,93],"performed":[44],"while":[45],"also":[46],"being":[47],"too":[48],"numerous":[49],"easily":[51],"visualize":[52],"or":[53],"compute":[54],"on.":[55],"recent":[58],"pair":[59],"publications":[61],"[1,2],":[62],"we":[63,116],"address":[64],"both":[65],"challenges":[68],"with":[69,97],"deep":[71],"neural":[72],"network":[73],"tensor":[74],"factorization":[75],"method,":[76],"Avocado,":[77],"compresses":[79],"into":[82],"dense,":[83],"information-rich":[84],"representations.":[85],"We":[86],"demonstrate":[87],"learned":[90,131],"representations":[91,132],"can":[92],"used":[94],"impute,":[96],"high":[98],"accuracy,":[99],"output":[101],"tens":[103],"have":[110],"not":[111],"yet":[112],"been":[113],"performed.":[114],"Further,":[115],"show":[117],"that,":[118],"on":[119,137],"variety":[121],"genomics":[123],"tasks,":[124],"machine":[125],"learning":[126],"models":[127],"leverage":[129],"outperform":[133],"those":[134],"trained":[135],"directly":[136],"measurements.":[140],"The":[141],"code":[142],"is":[143],"publicly":[144],"available":[145],"at":[146],"https://github.com/jmschrei/avocado.":[147]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-11-23T00:00:00"}