{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T17:53:57Z","timestamp":1760550837096},"reference-count":28,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2019,6]]},"abstract":"<jats:p> Cancer subtype identification is an unmet need in precision diagnosis. Recently, evolutionary conservation has been indicated to contain informative signatures for functional significance in cancers. However, the importance of evolutionary conservation in distinguishing cancer subtypes remains largely unclear. Here, we identified the evolutionarily conserved genes (i.e. core genes) and observed that they are primarily involved in cellular pathways relevant to cell growth and metabolisms. By using these core genes, we developed two novel strategies, namely a feature-based strategy (FES) and an image-based strategy (IMS) by integrating their evolutionary and genomic profiles with the deep learning algorithm. In comparison with the FES using the random set and the strategy using the PAM50 classifier, the core gene set-based FES achieved a higher accuracy for identifying breast cancer subtypes. The IMS and FES using the core gene set yielded better performances than the other strategies, in terms of classifying both breast cancer subtypes and multiple cancer types. Moreover, the IMS is reproducible even using different gene expression data (i.e. RNA-seq and microarray). Comprehensive analysis of eight cancer types demonstrates that our evolutionary conservation-based models represent a valid and helpful approach for identifying cancer subtypes and the core gene set offers distinguishable clues of cancer subtypes. <\/jats:p>","DOI":"10.1142\/s0219720019400055","type":"journal-article","created":{"date-parts":[[2019,5,10]],"date-time":"2019-05-10T05:44:12Z","timestamp":1557467052000},"page":"1940005","source":"Crossref","is-referenced-by-count":14,"title":["Deep learning with evolutionary and genomic profiles for identifying cancer subtypes"],"prefix":"10.1142","volume":"17","author":[{"given":"Chun-Yu","family":"Lin","sequence":"first","affiliation":[{"name":"Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 6110011, Japan"}]},{"given":"Peiying","family":"Ruan","sequence":"additional","affiliation":[{"name":"NVIDIA AI Technology Center, NVIDIA Corporation Japan, Tokyo 1070052, Japan"}]},{"given":"Ruiming","family":"Li","sequence":"additional","affiliation":[{"name":"Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 6110011, Japan"}]},{"given":"Jinn-Moon","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 300, Taiwan"}]},{"given":"Simon","family":"See","sequence":"additional","affiliation":[{"name":"NVIDIA AI Technology Center, NVIDIA Corporation Singapore, Singapore 138522, Singapore"}]},{"given":"Jiangning","family":"Song","sequence":"additional","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry &amp; Molecular Biology, Monash University, Melbourne, VIC 3800, Australia"}]},{"given":"Tatsuya","family":"Akutsu","sequence":"additional","affiliation":[{"name":"Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 6110011, Japan"}]}],"member":"219","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"S0219720019400055BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2017.01.018"},{"key":"S0219720019400055BIB002","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2764"},{"key":"S0219720019400055BIB003","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms9878"},{"key":"S0219720019400055BIB004","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1732912100"},{"key":"S0219720019400055BIB005","doi-asserted-by":"publisher","DOI":"10.1186\/s12920-017-0306-x"},{"key":"S0219720019400055BIB006","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.072"},{"key":"S0219720019400055BIB007","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.2147"},{"key":"S0219720019400055BIB008","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.78.11.6789"},{"key":"S0219720019400055BIB009","doi-asserted-by":"publisher","DOI":"10.1093\/gbe\/evw113"},{"key":"S0219720019400055BIB010","doi-asserted-by":"publisher","DOI":"10.1111\/eva.12417"},{"key":"S0219720019400055BIB011","doi-asserted-by":"publisher","DOI":"10.3390\/genes8070182"},{"key":"S0219720019400055BIB012","doi-asserted-by":"publisher","DOI":"10.1038\/srep09386"},{"key":"S0219720019400055BIB013","first-page":"1097","volume-title":"Proc. 25th Int Conf Neural Information Processing Systems","volume":"1","author":"Krizhevsky A","year":"2012"},{"key":"S0219720019400055BIB014","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gks1193"},{"key":"S0219720019400055BIB015","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/19.2.185"},{"key":"S0219720019400055BIB016","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gng015"},{"key":"S0219720019400055BIB017","doi-asserted-by":"publisher","DOI":"10.2202\/1544-6115.1027"},{"key":"S0219720019400055BIB018","doi-asserted-by":"publisher","DOI":"10.1038\/srep20518"},{"key":"S0219720019400055BIB019","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0122333"},{"key":"S0219720019400055BIB020","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajpath.2010.10.020"},{"key":"S0219720019400055BIB021","doi-asserted-by":"publisher","DOI":"10.1002\/gcc.20811"},{"key":"S0219720019400055BIB022","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccr.2011.08.024"},{"key":"S0219720019400055BIB023","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2323"},{"key":"S0219720019400055BIB024","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-06-4571"},{"key":"S0219720019400055BIB025","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0010312"},{"key":"S0219720019400055BIB026","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3005723"},{"key":"S0219720019400055BIB027","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2008.18.1370"},{"key":"S0219720019400055BIB028","doi-asserted-by":"publisher","DOI":"10.1038\/nature12624"}],"container-title":["Journal of Bioinformatics and Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0219720019400055","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T17:16:44Z","timestamp":1565111804000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0219720019400055"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6]]},"references-count":28,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2019,7,9]]},"published-print":{"date-parts":[[2019,6]]}},"alternative-id":["10.1142\/S0219720019400055"],"URL":"https:\/\/doi.org\/10.1142\/s0219720019400055","relation":{},"ISSN":["0219-7200","1757-6334"],"issn-type":[{"value":"0219-7200","type":"print"},{"value":"1757-6334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6]]}}}