{"id":"https://openalex.org/W2592839484","doi":"https://doi.org/10.1186/s12859-017-1546-7","title":"Positive-Unlabeled Learning for inferring drug interactions based on heterogeneous attributes","display_name":"Positive-Unlabeled Learning for inferring drug interactions based on heterogeneous attributes","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2592839484","doi":"https://doi.org/10.1186/s12859-017-1546-7","mag":"2592839484","pmid":"https://pubmed.ncbi.nlm.nih.gov/28249566"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-017-1546-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-017-1546-7","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-017-1546-7","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-017-1546-7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046123864","display_name":"Pathima Nusrath Hameed","orcid":"https://orcid.org/0000-0002-8118-9823"},"institutions":[{"id":"https://openalex.org/I128559575","display_name":"University of Ruhuna","ror":"https://ror.org/033jvzr14","country_code":"LK","type":"education","lineage":["https://openalex.org/I128559575"]},{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU","LK"],"is_corresponding":true,"raw_author_name":"Pathima Nusrath Hameed","raw_affiliation_strings":["Data61, Victoria Research Lab, West Melbourne, 3003, Australia. nusrath@dcs.ruh.ac.lk","Department of Computer Science, University of Ruhuna, Matara, 81000, Sri Lanka. nusrath@dcs.ruh.ac.lk","Department of Mechanical Engineering, University of Melbourne, Parkville, Melbourne, 3010, Australia. nusrath@dcs.ruh.ac.lk","Department of Mechanical Engineering, University of Melbourne, Parkville, Melbourne, 3010, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8118-9823","affiliations":[{"raw_affiliation_string":"Data61, Victoria Research Lab, West Melbourne, 3003, Australia. nusrath@dcs.ruh.ac.lk","institution_ids":["https://openalex.org/I42894916"]},{"raw_affiliation_string":"Department of Computer Science, University of Ruhuna, Matara, 81000, Sri Lanka. nusrath@dcs.ruh.ac.lk","institution_ids":["https://openalex.org/I128559575"]},{"raw_affiliation_string":"Department of Mechanical Engineering, University of Melbourne, Parkville, Melbourne, 3010, Australia. nusrath@dcs.ruh.ac.lk","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Department of Mechanical Engineering, University of Melbourne, Parkville, Melbourne, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067214173","display_name":"Karin Verspoor","orcid":"https://orcid.org/0000-0002-8661-1544"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Karin Verspoor","raw_affiliation_strings":["Department of Computing and Information Systems, University of Melbourne, Parkville, Melbourne, 3010, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computing and Information Systems, University of Melbourne, Parkville, Melbourne, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030282511","display_name":"Snezana Kusljic","orcid":"https://orcid.org/0000-0002-2465-9884"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I242743682","display_name":"Florey Institute of Neuroscience and Mental Health","ror":"https://ror.org/03a2tac74","country_code":"AU","type":"facility","lineage":["https://openalex.org/I165779595","https://openalex.org/I242743682"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Snezana Kusljic","raw_affiliation_strings":["Department of Nursing, University of Melbourne, Parkville, Melbourne, 3010, Australia","The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Melbourne, 3010, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Nursing, University of Melbourne, Parkville, Melbourne, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Melbourne, 3010, Australia","institution_ids":["https://openalex.org/I242743682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067418792","display_name":"Saman Halgamuge","orcid":"https://orcid.org/0000-0002-2536-4930"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Saman Halgamuge","raw_affiliation_strings":["Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, 2601, ACT, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra, 2601, ACT, Australia","institution_ids":["https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046123864"],"corresponding_institution_ids":["https://openalex.org/I128559575","https://openalex.org/I165779595","https://openalex.org/I42894916"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":{"value":2790,"currency":"USD","value_usd":2790},"fwci":5.524,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.96453935,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"18","issue":"1","first_page":"140","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.5958999991416931,"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":0.5958999991416931,"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/T10375","display_name":"Pharmacogenetics and Drug Metabolism","score":0.20649999380111694,"subfield":{"id":"https://openalex.org/subfields/3004","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.03240000084042549,"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/drugbank","display_name":"DrugBank","score":0.7700612545013428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6994218826293945},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.6660495400428772},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6532883048057556},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6359273195266724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5683755874633789},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.514910101890564},{"id":"https://openalex.org/keywords/drug-drug-interaction","display_name":"Drug-drug interaction","score":0.49810218811035156},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49478667974472046},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4847695231437683},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4377620220184326},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.40563130378723145},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.38952022790908813},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3788486123085022},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12971127033233643},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.10614416003227234}],"concepts":[{"id":"https://openalex.org/C155261790","wikidata":"https://www.wikidata.org/wiki/Q1122544","display_name":"DrugBank","level":3,"score":0.7700612545013428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6994218826293945},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.6660495400428772},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6532883048057556},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6359273195266724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5683755874633789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.514910101890564},{"id":"https://openalex.org/C2910466267","wikidata":"https://www.wikidata.org/wiki/Q718753","display_name":"Drug-drug interaction","level":3,"score":0.49810218811035156},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49478667974472046},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4847695231437683},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4377620220184326},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.40563130378723145},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.38952022790908813},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3788486123085022},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12971127033233643},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.10614416003227234},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D003577","descriptor_name":"Cytochrome P-450 Enzyme System","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D003577","descriptor_name":"Cytochrome P-450 Enzyme System","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D003577","descriptor_name":"Cytochrome P-450 Enzyme System","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D004347","descriptor_name":"Drug Interactions","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D020033","descriptor_name":"Protein Isoforms","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.1186/s12859-017-1546-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-017-1546-7","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-017-1546-7","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:28249566","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28249566","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:jupiter.its.unimelb.edu.au:11343/213525","is_oa":true,"landing_page_url":"http://hdl.handle.net/11343/213525","pdf_url":"http://hdl.handle.net/11343/213525","source":{"id":"https://openalex.org/S4377196259","display_name":"Minerva Access (University of Melbourne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165779595","host_organization_name":"The University of Melbourne","host_organization_lineage":["https://openalex.org/I165779595"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:5333429","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5333429","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"},{"id":"pmh:oai:figshare.com:article/27554862","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Positive-Unlabeled_Learning_for_inferring_drug_interactions_based_on_heterogeneous_attributes/27554862","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-017-1546-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-017-1546-7","pdf_url":"https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-017-1546-7","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.41999998688697815}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310369","display_name":"National ICT Australia","ror":"https://ror.org/03q397159"},{"id":"https://openalex.org/F4320320386","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07"},{"id":"https://openalex.org/F4320320974","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2592839484.pdf","grobid_xml":"https://content.openalex.org/works/W2592839484.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W22461475","https://openalex.org/W46659105","https://openalex.org/W84368778","https://openalex.org/W640820731","https://openalex.org/W1018047830","https://openalex.org/W1552830208","https://openalex.org/W1618905105","https://openalex.org/W1823976324","https://openalex.org/W1965887320","https://openalex.org/W1984054151","https://openalex.org/W1993387039","https://openalex.org/W2009313526","https://openalex.org/W2016210016","https://openalex.org/W2018518196","https://openalex.org/W2024985940","https://openalex.org/W2035977761","https://openalex.org/W2060609416","https://openalex.org/W2091439417","https://openalex.org/W2106417713","https://openalex.org/W2109482131","https://openalex.org/W2117397379","https://openalex.org/W2118978333","https://openalex.org/W2119002393","https://openalex.org/W2135037015","https://openalex.org/W2138028060","https://openalex.org/W2138275182","https://openalex.org/W2142572836","https://openalex.org/W2154896031","https://openalex.org/W2155157373","https://openalex.org/W2163352587","https://openalex.org/W2168701898","https://openalex.org/W2191189641","https://openalex.org/W2232501282","https://openalex.org/W2234741790","https://openalex.org/W2320155933","https://openalex.org/W2329271502","https://openalex.org/W2463669415","https://openalex.org/W2497965792","https://openalex.org/W2548695521","https://openalex.org/W2955261267","https://openalex.org/W3139821600","https://openalex.org/W3141738472","https://openalex.org/W4239414618","https://openalex.org/W4240348024","https://openalex.org/W4285719527","https://openalex.org/W6638684992","https://openalex.org/W6701905820"],"related_works":["https://openalex.org/W2013181441","https://openalex.org/W4226316650","https://openalex.org/W4205564556","https://openalex.org/W2292935574","https://openalex.org/W2887372993","https://openalex.org/W2251104810","https://openalex.org/W4200351086","https://openalex.org/W2782660323","https://openalex.org/W4291302307","https://openalex.org/W3170311506"],"abstract_inverted_index":{"BACKGROUND:":[0],"Investigating":[1],"and":[2,36,47,61,152,216,272,301],"understanding":[3],"drug-drug":[4],"interactions":[5,218],"(DDIs)":[6],"is":[7,40],"important":[8],"in":[9,44,199,236,268,274],"improving":[10],"the":[11,84,134,145,170,196,208,223,230,254,277,290,306,322],"effectiveness":[12],"of":[13,103,120,125,150,233,257,270,292,325],"clinical":[14,255,317],"care.":[15],"DDIs":[16,165,210,251,300,304],"can":[17,76,312],"occur":[18],"when":[19],"two":[20],"or":[21,86],"more":[22],"drugs":[23,151],"are":[24,72,97,179,190],"administered":[25],"together.":[26],"Experimentally":[27],"based":[28],"DDI":[29,67,203],"detection":[30],"methods":[31,50],"require":[32,58],"a":[33,41,66,107,139,244],"large":[34],"cost":[35],"time.":[37],"Hence,":[38],"there":[39],"great":[42],"interest":[43],"developing":[45],"efficient":[46],"useful":[48],"computational":[49],"for":[51,63,80,111,159,195,202],"inferring":[52,112,160],"potential":[53,113],"DDIs.":[54,114,161],"Standard":[55],"binary":[56,200],"classifiers":[57],"both":[59],"positives":[60,79],"negatives":[62,85,132],"training.":[64],"In":[65],"context,":[68],"drug":[69,87,176,188,326],"pairs":[70,88,177,189],"that":[71,89,178,279],"known":[73],"to":[74,93,130,143,181,229,252,276,315],"interact":[75,183],"serve":[77],"as":[78,192,211,285,319,321],"predictive":[81],"methods.":[82],"But,":[83],"have":[90,94],"been":[91],"confirmed":[92],"no":[95],"interaction":[96,239],"scarce.":[98],"To":[99],"address":[100],"this":[101,258],"lack":[102],"negatives,":[104,287],"we":[105,173,206,242],"introduce":[106],"Positive-Unlabeled":[108],"Learning":[109],"method":[110,118,278],"RESULTS:":[115],"The":[116],"proposed":[117,171,262],"consists":[119],"three":[121,248],"steps:":[122],"i)":[123],"application":[124],"Growing":[126,224],"Self":[127,225],"Organizing":[128,226],"Maps":[129],"infer":[131],"from":[133,166],"unlabeled":[135,282],"dataset;":[136],"ii)":[137],"using":[138,154],"pairwise":[140],"similarity":[141,293],"function":[142],"quantify":[144],"overlap":[146],"between":[147],"individual":[148],"features":[149],"iii)":[153],"support":[155],"vector":[156],"machine":[157],"classifier":[158],"We":[162,295],"obtained":[163],"6036":[164],"DrugBank":[167],"database.":[168],"Using":[169],"approach,":[172],"inferred":[174,296],"589":[175],"likely":[180,286],"not":[182],"with":[184,305],"each":[185],"other;":[186],"these":[187,234],"used":[191,314],"representative":[193],"data":[194,283],"negative":[197],"class":[198],"classification":[201],"prediction.":[204],"Moreover,":[205],"classify":[207],"predicted":[209,249],"Cytochrome":[212],"P450":[213],"(CYP)":[214],"enzyme-Dependent":[215],"CYP-Independent":[217,303],"invoking":[219],"their":[220],"locations":[221],"on":[222,247,289],"Map,":[227],"due":[228],"particular":[231],"importance":[232],"enzymes":[235],"clinically":[237],"significant":[238],"effects.":[240],"Further,":[241],"provide":[243],"case":[245],"study":[246],"CYP-Dependent":[250,299],"evaluate":[253],"relevance":[256],"study.":[259],"CONCLUSION:":[260],"Our":[261,310],"approach":[263],"showed":[264],"an":[265],"absolute":[266],"improvement":[267],"F1-score":[269],"14":[271],"38%":[273],"comparison":[275],"randomly":[280],"selects":[281],"points":[284],"depending":[288],"choice":[291],"function.":[294],"5300":[297],"possible":[298],"592":[302],"highest":[307],"posterior":[308],"probabilities.":[309],"discoveries":[311],"be":[313],"improve":[316],"care":[318],"well":[320],"research":[323],"outcomes":[324],"development.":[327]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}