{"title":"计算疾病进展模型可以提供对癌症进化的见解。","authors":"Steve Goodison, Mark E Sherman, Yijun Sun","doi":"10.18632/oncoscience.501","DOIUrl":null,"url":null,"abstract":"Steve Goodison1, Mark E. Sherman1, Yijun Sun2,3,4 1 Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA 2 Department of Microbiology and Immunology, The State University of New York, Buffalo, NY, USA 3 Department of Computer Science and Engineering, The State University of New York, Buffalo, NY, USA 4 Department of Biostatistics, The State University of New York, Buffalo, NY, USA","PeriodicalId":19508,"journal":{"name":"Oncoscience","volume":"7 3-4","pages":"21-22"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217135/pdf/","citationCount":"1","resultStr":"{\"title\":\"Computational disease progression modeling can provide insights into cancer evolution.\",\"authors\":\"Steve Goodison, Mark E Sherman, Yijun Sun\",\"doi\":\"10.18632/oncoscience.501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Steve Goodison1, Mark E. Sherman1, Yijun Sun2,3,4 1 Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA 2 Department of Microbiology and Immunology, The State University of New York, Buffalo, NY, USA 3 Department of Computer Science and Engineering, The State University of New York, Buffalo, NY, USA 4 Department of Biostatistics, The State University of New York, Buffalo, NY, USA\",\"PeriodicalId\":19508,\"journal\":{\"name\":\"Oncoscience\",\"volume\":\"7 3-4\",\"pages\":\"21-22\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217135/pdf/\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Oncoscience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18632/oncoscience.501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oncoscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18632/oncoscience.501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/3/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Computational disease progression modeling can provide insights into cancer evolution.
Steve Goodison1, Mark E. Sherman1, Yijun Sun2,3,4 1 Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA 2 Department of Microbiology and Immunology, The State University of New York, Buffalo, NY, USA 3 Department of Computer Science and Engineering, The State University of New York, Buffalo, NY, USA 4 Department of Biostatistics, The State University of New York, Buffalo, NY, USA