{"id":"https://openalex.org/W2197241765","doi":"https://doi.org/10.1371/journal.pcbi.1004498","title":"Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model","display_name":"Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model","publication_year":2015,"publication_date":"2015-09-29","ids":{"openalex":"https://openalex.org/W2197241765","doi":"https://doi.org/10.1371/journal.pcbi.1004498","mag":"2197241765","pmid":"https://pubmed.ncbi.nlm.nih.gov/26418249"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pcbi.1004498","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1004498","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004498&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004498&type=printable","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081128142","display_name":"Naiqian Zhang","orcid":"https://orcid.org/0000-0003-0800-0016"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Naiqian Zhang","raw_affiliation_strings":["Department of Mathematics, Shanghai Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100601473","display_name":"Haiyun Wang","orcid":"https://orcid.org/0000-0001-8364-8328"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyun Wang","raw_affiliation_strings":["Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059682426","display_name":"Yun Fang","orcid":"https://orcid.org/0000-0001-7377-6780"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Fang","raw_affiliation_strings":["Department of Mathematics, Shanghai Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384782","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-6710-9823"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Department of Mathematics, Shanghai Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021047181","display_name":"Xiaoqi Zheng","orcid":"https://orcid.org/0000-0002-1832-4404"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoqi Zheng","raw_affiliation_strings":["Department of Mathematics, Shanghai Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045575546","display_name":"X. Shirley Liu","orcid":"https://orcid.org/0000-0003-4736-7339"},"institutions":[{"id":"https://openalex.org/I4210117453","display_name":"Dana-Farber Cancer Institute","ror":"https://ror.org/02jzgtq86","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210117453"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"X. Shirley Liu","raw_affiliation_strings":["Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America","Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America","Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America","institution_ids":[]},{"raw_affiliation_string":"Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America","institution_ids":["https://openalex.org/I4210117453"]},{"raw_affiliation_string":"Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America","institution_ids":["https://openalex.org/I4210117453"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021047181","https://openalex.org/A5045575546","https://openalex.org/A5100384782"],"corresponding_institution_ids":["https://openalex.org/I21945476","https://openalex.org/I4210117453"],"apc_list":{"value":2655,"currency":"USD","value_usd":2655},"apc_paid":{"value":2655,"currency":"USD","value_usd":2655},"fwci":17.2928,"has_fulltext":true,"cited_by_count":226,"citation_normalized_percentile":{"value":0.99437743,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"11","issue":"9","first_page":"e1004498","last_page":"e1004498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"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":1.0,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9973999857902527,"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/T11533","display_name":"Melanoma and MAPK Pathways","score":0.9955999851226807,"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/cancer-cell-lines","display_name":"Cancer cell lines","score":0.6876875162124634},{"id":"https://openalex.org/keywords/drug-response","display_name":"Drug response","score":0.6044729948043823},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.4729818105697632},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.45671525597572327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38765570521354675},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.33828288316726685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.330142080783844},{"id":"https://openalex.org/keywords/cancer-cell","display_name":"Cancer cell","score":0.25627464056015015},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2530551254749298},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.1222391426563263},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.09904113411903381}],"concepts":[{"id":"https://openalex.org/C2994372470","wikidata":"https://www.wikidata.org/wiki/Q4118072","display_name":"Cancer cell lines","level":4,"score":0.6876875162124634},{"id":"https://openalex.org/C2994119904","wikidata":"https://www.wikidata.org/wiki/Q1251001","display_name":"Drug response","level":3,"score":0.6044729948043823},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.4729818105697632},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.45671525597572327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38765570521354675},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.33828288316726685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.330142080783844},{"id":"https://openalex.org/C96232424","wikidata":"https://www.wikidata.org/wiki/Q4118072","display_name":"Cancer cell","level":3,"score":0.25627464056015015},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2530551254749298},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.1222391426563263},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.09904113411903381}],"mesh":[{"descriptor_ui":"D000970","descriptor_name":"Antineoplastic Agents","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":false},{"descriptor_ui":"D000970","descriptor_name":"Antineoplastic Agents","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":false},{"descriptor_ui":"D000970","descriptor_name":"Antineoplastic Agents","qualifier_ui":"Q000494","qualifier_name":"pharmacology","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":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D045744","descriptor_name":"Cell Line, Tumor","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":6,"locations":[{"id":"doi:10.1371/journal.pcbi.1004498","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1004498","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004498&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},{"id":"pmid:26418249","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26418249","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":"PLoS computational biology","raw_type":null},{"id":"pmh:oai:RePEc:plo:pcbi00:1004498","is_oa":false,"landing_page_url":"https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004498","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:242e14e99d9247f7983ea062af0faca8","is_oa":false,"landing_page_url":"https://doaj.org/article/242e14e99d9247f7983ea062af0faca8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Computational Biology, Vol 11, Iss 9, p e1004498 (2015)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:3569740","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4587957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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"},{"id":"pmh:oai:figshare.com:article/1559737","is_oa":true,"landing_page_url":"https://figshare.com/articles/dataset/_Predicting_Anticancer_Drug_Responses_Using_a_Dual_Layer_Integrated_Cell_Line_Drug_Network_Model_/1559737","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"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":"","raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.1371/journal.pcbi.1004498","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1004498","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004498&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G3957733208","display_name":null,"funder_award_id":"GM099409","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G8759550867","display_name":null,"funder_award_id":"R01 GM099409","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320321881","display_name":"Shanghai Municipal Education Commission","ror":"https://ror.org/05tewj457"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2197241765.pdf","grobid_xml":"https://content.openalex.org/works/W2197241765.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W17970349","https://openalex.org/W2004638738","https://openalex.org/W2008319567","https://openalex.org/W2008345619","https://openalex.org/W2011474181","https://openalex.org/W2018570668","https://openalex.org/W2018663224","https://openalex.org/W2033525264","https://openalex.org/W2039872518","https://openalex.org/W2042445733","https://openalex.org/W2043398720","https://openalex.org/W2045293701","https://openalex.org/W2050810479","https://openalex.org/W2050934134","https://openalex.org/W2052468572","https://openalex.org/W2087312216","https://openalex.org/W2097498614","https://openalex.org/W2101030885","https://openalex.org/W2108933868","https://openalex.org/W2114759909","https://openalex.org/W2118529059","https://openalex.org/W2120204563","https://openalex.org/W2125789330","https://openalex.org/W2127553917","https://openalex.org/W2129860849","https://openalex.org/W2135007932","https://openalex.org/W2155626151","https://openalex.org/W2157697073","https://openalex.org/W2159887157","https://openalex.org/W2167395325","https://openalex.org/W2167736999","https://openalex.org/W2331260641"],"related_works":["https://openalex.org/W4206379684","https://openalex.org/W2186113122","https://openalex.org/W1523310174","https://openalex.org/W2531913951","https://openalex.org/W2366105490","https://openalex.org/W1997438133","https://openalex.org/W2321880618","https://openalex.org/W3117207241","https://openalex.org/W2318806991","https://openalex.org/W2197241765"],"abstract_inverted_index":{"The":[0],"ability":[1],"to":[2,10,25,30,57,89,136,192,236],"predict":[3,90],"the":[4,61,91,104,137,145,173,177,185,195,201,206],"response":[5,93,155,198],"of":[6,38,94],"a":[7,11,15,67,95,100,128,132,157],"cancer":[8,39],"patient":[9],"therapeutic":[12],"agent":[13],"is":[14,169],"major":[16],"goal":[17],"in":[18,194,200],"modern":[19],"oncology":[20],"that":[21,43,222],"should":[22],"ultimately":[23],"lead":[24],"personalized":[26],"treatment.":[27],"Existing":[28],"approaches":[29],"predicting":[31],"drug":[32,62,84,92,197],"sensitivity":[33],"rely":[34],"primarily":[35],"on":[36],"profiling":[37],"cell":[40,70,77,97,187,209,225,234],"line":[41,78,98],"panels":[42],"have":[44,182],"been":[45],"treated":[46],"with":[47,122,162],"different":[48],"drugs":[49],"and":[50,83,110,126,151],"selecting":[51],"genomic":[52,55],"or":[53,59,124],"functional":[54],"features":[56],"regress":[58],"classify":[60],"response.":[63],"Here,":[64],"we":[65],"propose":[66],"dual-layer":[68,146,186,207],"integrated":[69,189,208],"line-drug":[71,188,210],"network":[72,80,86,190,211],"model,":[73],"which":[74,168],"uses":[75],"both":[76,149],"similarity":[79,85],"(CSN)":[81],"data":[82,88],"(DSN)":[87],"given":[96],"using":[99,144,176],"weighted":[101],"model.":[102,142,180],"Using":[103],"Cancer":[105,111],"Cell":[106],"Line":[107],"Encyclopedia":[108],"(CCLE)":[109],"Genome":[112],"Project":[113],"(CGP)":[114],"studies":[115],"as":[116],"benchmark":[117],"datasets,":[118],"our":[119,153],"single-layer":[120],"model":[121,147,191,212,216],"CSN":[123,150],"DSN":[125],"only":[127],"single":[129],"parameter":[130],"achieved":[131],"prediction":[133],"performance":[134],"comparable":[135],"previously":[138],"generated":[139],"elastic":[140,178],"net":[141,179],"When":[143],"integrating":[148],"DSN,":[152],"predicted":[154,221],"reached":[156],"0.6":[158],"Pearson":[159],"correlation":[160],"coefficient":[161],"observed":[163],"responses":[164],"for":[165],"most":[166],"drugs,":[167],"significantly":[170],"better":[171],"than":[172,231],"previous":[174],"results":[175],"We":[181],"also":[183],"applied":[184],"fill":[193],"missing":[196],"values":[199],"CGP":[202],"dataset.":[203],"Even":[204],"though":[205],"does":[213],"not":[214],"specifically":[215],"mutation":[217],"information,":[218],"it":[219],"correctly":[220],"BRAF":[223,232],"mutant":[224],"lines":[226,235],"would":[227],"be":[228],"more":[229],"sensitive":[230],"wild-type":[233],"three":[237],"MEK1/2":[238],"inhibitors":[239],"tested.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":24},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":13}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}