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An integrated clinical and genomic information system for cancer precision medicine
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Yeongjun | - |
dc.contributor.author | Choi, Taekjin | - |
dc.contributor.author | Kim, Jongho | - |
dc.contributor.author | Park, Jisub | - |
dc.contributor.author | Seo, Jihae | - |
dc.contributor.author | Kim, Sangok | - |
dc.contributor.author | Kwon, Yeajee | - |
dc.contributor.author | Lee, Seungjae | - |
dc.contributor.author | Lee, Sanghyuk | - |
dc.date.accessioned | 2018-05-29T05:26:45Z | - |
dc.date.available | 2018-05-29T14:27:48Z | - |
dc.date.issued | 2018-04-20 | - |
dc.identifier.citation | BMC Medical Genomics, 11(Suppl 2):34 | ko_KR |
dc.identifier.issn | 1755-8794 | - |
dc.identifier.uri | https://hdl.handle.net/10371/142631 | - |
dc.description.abstract | Background
Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patients genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly. Results Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data. Conclusions Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology. | ko_KR |
dc.description.sponsorship | The publication cost of this article was funded by the Technology Innovation Program of the Ministry of Trade, Industry and Energy, Republic of Korea (10050154). | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BioMed Central | ko_KR |
dc.subject | Information system | ko_KR |
dc.subject | Genomic medicine | ko_KR |
dc.subject | Personalized medicine | ko_KR |
dc.subject | Precision medicine | ko_KR |
dc.subject | Targeted therapy | ko_KR |
dc.subject | Oncology | ko_KR |
dc.subject | Cancer | ko_KR |
dc.title | An integrated clinical and genomic information system for cancer precision medicine | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 장영준 | - |
dc.contributor.AlternativeAuthor | 최택진 | - |
dc.contributor.AlternativeAuthor | 김종호 | - |
dc.contributor.AlternativeAuthor | 박지섭 | - |
dc.contributor.AlternativeAuthor | 서지혜 | - |
dc.contributor.AlternativeAuthor | 김상옥 | - |
dc.contributor.AlternativeAuthor | 권예지 | - |
dc.contributor.AlternativeAuthor | 이승재 | - |
dc.contributor.AlternativeAuthor | 이상혁 | - |
dc.identifier.doi | 10.1186/s12920-018-0347-9 | - |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s). | - |
dc.date.updated | 2018-04-22T03:32:07Z | - |
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