{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T12:59:16Z","timestamp":1780405156208,"version":"3.54.1"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2017,7,12]],"date-time":"2017-07-12T00:00:00Z","timestamp":1499817600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["296516"],"award-info":[{"award-number":["296516"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["272577"],"award-info":[{"award-number":["272577"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["277293"],"award-info":[{"award-number":["277293"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["269862"],"award-info":[{"award-number":["269862"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["272437"],"award-info":[{"award-number":["272437"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["279163"],"award-info":[{"award-number":["279163"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["292611"],"award-info":[{"award-number":["292611"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["295504"],"award-info":[{"award-number":["295504"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006383","name":"Cancer Society of Finland","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006383","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006306","name":"Sigrid Jus\u00e9lius Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006306","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>A prime challenge in precision cancer medicine is to identify genomic and molecular features that are predictive of drug treatment responses in cancer cells. Although there are several computational models for accurate drug response prediction, these often lack the ability to infer which feature combinations are the most predictive, particularly for high-dimensional molecular datasets. As increasing amounts of diverse genome-wide data sources are becoming available, there is a need to build new computational models that can effectively combine these data sources and identify maximally predictive feature combinations.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We present a novel approach that leverages on systematic integration of data sources to identify response predictive features of multiple drugs. To solve the modeling task we implement a Bayesian linear regression method. To further improve the usefulness of the proposed model, we exploit the known human cancer kinome for identifying biologically relevant feature combinations. In case studies with a synthetic dataset and two publicly available cancer cell line datasets, we demonstrate the improved accuracy of our method compared to the widely used approaches in drug response analysis. As key examples, our model identifies meaningful combinations of features for the well known EGFR, ALK, PLK and PDGFR inhibitors.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>The source code of the method is available at https:\/\/github.com\/suleimank\/mvlr.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx266","type":"journal-article","created":{"date-parts":[[2017,4,20]],"date-time":"2017-04-20T07:52:13Z","timestamp":1492674733000},"page":"i359-i368","source":"Crossref","is-referenced-by-count":65,"title":["Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression"],"prefix":"10.1093","volume":"33","author":[{"given":"Muhammad","family":"Ammad-ud-din","sequence":"first","affiliation":[{"name":"Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland"},{"name":"Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suleiman A","family":"Khan","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland"},{"name":"Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Krister","family":"Wennerberg","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tero","family":"Aittokallio","sequence":"additional","affiliation":[{"name":"Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland"},{"name":"Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland"},{"name":"Department of Mathematics and Statistics, University of Turku, Turku, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,7,12]]},"reference":[{"key":"2023051506504270400_btx266-B1","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1021\/ci500152b","article-title":"Integrative and personalized QSAR analysis in cancer by Kernelized Bayesian matrix factorization","volume":"54","author":"Ammad-Ud Din","year":"2014","journal-title":"J. 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