{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T01:39:40Z","timestamp":1772847580552,"version":"3.50.1"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T00:00:00Z","timestamp":1642377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32170650"],"award-info":[{"award-number":["32170650"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31911530148"],"award-info":[{"award-number":["31911530148"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32170656"],"award-info":[{"award-number":["32170656"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangzhou and Guangdong Key Project","award":["202007030002"],"award-info":[{"award-number":["202007030002"]}]},{"name":"Guangzhou and Guangdong Key Project","award":["2018B030335001"],"award-info":[{"award-number":["2018B030335001"]}]},{"name":"Clinical Medicine Plus X - Young Scholars Project, Peking University"},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["PKU2021LCXQ015"],"award-info":[{"award-number":["PKU2021LCXQ015"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009399","name":"Peking University Third Hospital","doi-asserted-by":"publisher","award":["BYSYYZD2021001"],"award-info":[{"award-number":["BYSYYZD2021001"]}],"id":[{"id":"10.13039\/501100009399","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein\u2013protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http:\/\/159.226.67.237\/sun\/cancer_driver\/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.<\/jats:p>","DOI":"10.1093\/bib\/bbab548","type":"journal-article","created":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T12:07:22Z","timestamp":1638274042000},"source":"Crossref","is-referenced-by-count":36,"title":["Comprehensive evaluation of computational methods for predicting cancer driver genes"],"prefix":"10.1093","volume":"23","author":[{"given":"Xiaohui","family":"Shi","sequence":"first","affiliation":[{"name":"Beijing Institutes of Life Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100080, China"}]},{"given":"Huajing","family":"Teng","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) at Peking University Cancer Hospital and Institute, Beijing 100080, China"}]},{"given":"Leisheng","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100080, China"}]},{"given":"Wenjian","family":"Bi","sequence":"additional","affiliation":[{"name":"Department of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing 100080, China"}]},{"given":"Wenqing","family":"Wei","sequence":"additional","affiliation":[{"name":"Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100080, China"}]},{"given":"Fengbiao","family":"Mao","sequence":"additional","affiliation":[{"name":"Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing 100080, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1992-2681","authenticated-orcid":false,"given":"Zhongsheng","family":"Sun","sequence":"additional","affiliation":[{"name":"Beijing Institutes of Life Science, Chinese Academy of Sciences, CAS Center for Excellence in Biotic Interactions and State Key Laboratory of Integrated Management of Pest Insects and Rodents, University of Chinese Academy of Sciences, Institute of Genomic Medicine, Wenzhou Medical University, IBMC-BGI Center, the Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Beijing 100080, China"}]}],"member":"286","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"key":"2022031506230796100_ref1","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1038\/nature07943","article-title":"The cancer genome","volume":"458","author":"Stratton","year":"2009","journal-title":"Nature"},{"key":"2022031506230796100_ref2","doi-asserted-by":"crossref","first-page":"1546","DOI":"10.1126\/science.1235122","article-title":"Cancer genome 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