{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T10:10:08Z","timestamp":1784110208757,"version":"3.55.0"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2017,1,18]],"date-time":"2017-01-18T00:00:00Z","timestamp":1484697600000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"name":"Key Projects of Hunan Province","award":["2015SK2037"],"award-info":[{"award-number":["2015SK2037"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81372516"],"award-info":[{"award-number":["81372516"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004761","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"crossref","award":["2016JJ5013"],"award-info":[{"award-number":["2016JJ5013"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Exploring the potential curative effects of drugs is crucial for effective drug development. Previous studies have indicated that integration of multiple types of information could be conducive to discovering novel indications of drugs. However, how to efficiently identify the mechanism behind drug\u2013disease associations while integrating data from different sources remains a challenging problem.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this research, we present a novel method for indication prediction of both new drugs and approved drugs. This method is based on Laplacian regularized sparse subspace learning (LRSSL), which integrates drug chemical information, drug target domain information and target annotation information. Experimental results show that the proposed method outperforms several recent approaches for predicting drug\u2013disease associations. Some drug therapeutic effects predicted by the method could be validated by database records or literatures. Moreover, with L1-norm constraint, important drug features have been extracted from multiple drug feature profiles. Case studies suggest that the extracted drug features could be beneficial to interpretation of the predicted results.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>https:\/\/github.com\/LiangXujun\/LRSSL<\/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\/btw770","type":"journal-article","created":{"date-parts":[[2016,12,2]],"date-time":"2016-12-02T12:05:39Z","timestamp":1480680339000},"page":"1187-1196","source":"Crossref","is-referenced-by-count":165,"title":["LRSSL: predict and interpret drug\u2013disease associations based on data integration using sparse subspace learning"],"prefix":"10.1093","volume":"33","author":[{"given":"Xujun","family":"Liang","sequence":"first","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengfei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Yan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Fu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Peng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingzhi","family":"Qu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiying","family":"Shao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuchu","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, XiangYa Hospital, Central South University, ChangSha, HuNan, People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,1,17]]},"reference":[{"key":"2023020205004453700_btw770-B1","first-page":"43","author":"Breese","year":"1998"},{"key":"2023020205004453700_btw770-B2","first-page":"197","article-title":"128 cases of myasthenia gravis treated with huperzine A","volume":"5","author":"Cheng","year":"1986","journal-title":"Chin. 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