{"id":"https://openalex.org/W3137188301","doi":"https://doi.org/10.1109/bigdata50022.2020.9378164","title":"Graph Neural Networks for COVID-19 Drug Discovery","display_name":"Graph Neural Networks for COVID-19 Drug Discovery","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3137188301","doi":"https://doi.org/10.1109/bigdata50022.2020.9378164","mag":"3137188301"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378164","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378164","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378164.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378164.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002480344","display_name":"Mark Cheung","orcid":"https://orcid.org/0000-0002-5909-8853"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Cheung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045861415","display_name":"Jos\u00e9 M. F. Moura","orcid":"https://orcid.org/0000-0002-9822-8294"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jose M. F. Moura","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.7486,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88582848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5646","last_page":"5648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9797999858856201,"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/drug-discovery","display_name":"Drug discovery","score":0.6889944672584534},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6879768967628479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5739510655403137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5571216344833374},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5463179349899292},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.5092126131057739},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5054833889007568},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.4911074638366699},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48216956853866577},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19947880506515503},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.17871642112731934},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.17564356327056885}],"concepts":[{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.6889944672584534},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879768967628479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5739510655403137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5571216344833374},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5463179349899292},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.5092126131057739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5054833889007568},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.4911074638366699},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48216956853866577},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19947880506515503},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.17871642112731934},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.17564356327056885},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378164","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378164","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378164.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/bigdata50022.2020.9378164","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378164","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378164.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310207","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3137188301.pdf","grobid_xml":"https://content.openalex.org/works/W3137188301.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2290847742","https://openalex.org/W2606780347","https://openalex.org/W2765323781","https://openalex.org/W2801991413","https://openalex.org/W2964015378","https://openalex.org/W2966357564","https://openalex.org/W3007309629","https://openalex.org/W3041698787","https://openalex.org/W3047391881","https://openalex.org/W3086427314","https://openalex.org/W3087156149","https://openalex.org/W3096934581","https://openalex.org/W3100157108","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6745316256","https://openalex.org/W6780622884"],"related_works":["https://openalex.org/W2086397253","https://openalex.org/W4375867731","https://openalex.org/W2133122801","https://openalex.org/W600422426","https://openalex.org/W2007156430","https://openalex.org/W2170882281","https://openalex.org/W3081478936","https://openalex.org/W2611989081","https://openalex.org/W2480711475","https://openalex.org/W2785612136"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2,44],"led":[3],"to":[4,32],"major":[5],"advances":[6],"in":[7,65,99,149],"fields":[8,23],"like":[9],"natural":[10],"language":[11],"processing,":[12],"computer":[13],"vision,":[14],"and":[15,126],"other":[16],"Euclidean":[17],"data":[18,25],"domains.":[19],"Yet,":[20],"many":[21],"important":[22],"have":[24],"defined":[26],"on":[27,77,130],"irregular":[28],"domains,":[29],"requiring":[30],"graphs":[31],"be":[33],"explicitly":[34],"modeled.":[35],"One":[36],"such":[37],"application":[38],"is":[39],"drug":[40,120],"discovery.":[41],"Recently,":[42],"research":[43],"found":[45],"that":[46,84],"using":[47,60],"graph":[48],"neural":[49],"network":[50],"(GNN)":[51],"models,":[52],"given":[53],"enough":[54],"data,":[55],"can":[56,85],"perform":[57],"better":[58],"than":[59],"human-engineered":[61],"fingerprints":[62],"or":[63],"descriptors":[64],"predicting":[66,78],"molecular":[67,80],"properties":[68,81],"of":[69,107,118,140],"potential":[70],"antibiotics.We":[71],"explore":[72],"these":[73],"state-of-the-art":[74],"AI":[75],"models":[76,93],"desirable":[79],"for":[82,142],"drugs":[83],"inhibit":[86],"SARS-CoV-2.":[87],"We":[88],"build":[89],"upon":[90],"the":[91,105,108,119],"GNN":[92],"with":[94],"ideas":[95],"from":[96],"recent":[97],"breakthroughs":[98],"geometric":[100],"deep":[101],"learning,":[102],"inspired":[103],"by":[104],"topologies":[106],"molecules.":[109],"In":[110],"this":[111],"poster":[112],"paper,":[113],"we":[114],"present":[115],"an":[116],"overview":[117],"discovery":[121],"framework,":[122,125],"drug-target":[123],"interaction":[124],"GNNs.":[127],"Preliminary":[128],"results":[129],"two":[131],"COVID-19":[132],"related":[133],"datasets":[134],"are":[135],"encouraging,":[136],"achieving":[137],"a":[138],"ROC-AUC":[139],"0.72":[141],"FDA-approved":[143],"chemical":[144],"library":[145],"screened":[146],"against":[147],"SARS-CoV-2":[148],"vitro.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}