{"title":"RUN-ONCO:一个高度可扩展的癌症精准医疗软件平台","authors":"Neda Peyrone, D. Wichadakul","doi":"10.1145/3375923.3375928","DOIUrl":null,"url":null,"abstract":"Precision medicine is a strategy to personalize disease identification and medical care decisions through genetics. The rapid development of -omics technologies e.g., DNA and RNA sequencing, which reveal specific gene mutations in a patient's tumor or profiling of gene expressions for drug responses helps oncologists find effective treatments for individual patients based on their genetics. Hence, besides the clinical records, -omics data become essential for personalized diagnosis and treatments. In this paper, a web-based standalone software platform for cancer precision medicine, called RUN-ONCO, is proposed aiming to help oncologists and researchers manage and make use of the available clinical and -omics data easily and efficiently. The platform allows the management of clinical records, biospecimens, and -omics data and enables various integrative data analyses together with public databases such as STRING and OncoKB. With the increasing number of published methods for various -omics data analyses together with the availability of numerous javascript libraries for data visualization, RUN-ONCO has also been designed to be highly extensible with plugins for both visualizations and analysis methods. A demo version of RUN-ONCO is available online at http://cucpbioinfo.cp.eng.chula.ac.th:6002 and the source code for local deployment is at https://gitlab.com/peyrone/run-onco.","PeriodicalId":20457,"journal":{"name":"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"RUN-ONCO: A Highly Extensible Software Platform for Cancer Precision Medicine\",\"authors\":\"Neda Peyrone, D. Wichadakul\",\"doi\":\"10.1145/3375923.3375928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Precision medicine is a strategy to personalize disease identification and medical care decisions through genetics. The rapid development of -omics technologies e.g., DNA and RNA sequencing, which reveal specific gene mutations in a patient's tumor or profiling of gene expressions for drug responses helps oncologists find effective treatments for individual patients based on their genetics. Hence, besides the clinical records, -omics data become essential for personalized diagnosis and treatments. In this paper, a web-based standalone software platform for cancer precision medicine, called RUN-ONCO, is proposed aiming to help oncologists and researchers manage and make use of the available clinical and -omics data easily and efficiently. The platform allows the management of clinical records, biospecimens, and -omics data and enables various integrative data analyses together with public databases such as STRING and OncoKB. With the increasing number of published methods for various -omics data analyses together with the availability of numerous javascript libraries for data visualization, RUN-ONCO has also been designed to be highly extensible with plugins for both visualizations and analysis methods. A demo version of RUN-ONCO is available online at http://cucpbioinfo.cp.eng.chula.ac.th:6002 and the source code for local deployment is at https://gitlab.com/peyrone/run-onco.\",\"PeriodicalId\":20457,\"journal\":{\"name\":\"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3375923.3375928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3375923.3375928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
RUN-ONCO: A Highly Extensible Software Platform for Cancer Precision Medicine
Precision medicine is a strategy to personalize disease identification and medical care decisions through genetics. The rapid development of -omics technologies e.g., DNA and RNA sequencing, which reveal specific gene mutations in a patient's tumor or profiling of gene expressions for drug responses helps oncologists find effective treatments for individual patients based on their genetics. Hence, besides the clinical records, -omics data become essential for personalized diagnosis and treatments. In this paper, a web-based standalone software platform for cancer precision medicine, called RUN-ONCO, is proposed aiming to help oncologists and researchers manage and make use of the available clinical and -omics data easily and efficiently. The platform allows the management of clinical records, biospecimens, and -omics data and enables various integrative data analyses together with public databases such as STRING and OncoKB. With the increasing number of published methods for various -omics data analyses together with the availability of numerous javascript libraries for data visualization, RUN-ONCO has also been designed to be highly extensible with plugins for both visualizations and analysis methods. A demo version of RUN-ONCO is available online at http://cucpbioinfo.cp.eng.chula.ac.th:6002 and the source code for local deployment is at https://gitlab.com/peyrone/run-onco.