登入選單
返回Google圖書搜尋
Biomedical Informatics in Translational Research
Hai HuMichael Liebman
出版Artech House, 2008
主題Computers / Security / GeneralMEDICAL / Allied Health Services / Medical TechnologyMEDICAL / BiotechnologyMEDICAL / Family & General PracticeMEDICAL / Lasers in MedicineMedical / PharmacologyMedical / ResearchMedical / InformaticsScience / BioinformaticsTechnology & Engineering / Biomedical
ISBN159693039X9781596930391
URLhttp://books.google.com.hk/books?id=D_kcun73AzgC&hl=&source=gbs_api
EBookSAMPLE
註釋This groundbreaking resource on biomedical informatics gives you step-by-step insight into innovative techniques for integrating and federating data from clinical and high-throughput molecular study platforms as well as from the public domain. It details how to apply computational and statistical technologies to clinical, genomic, and proteomic studies to enhance data collection, tracking, storage, visualization, analysis, and knowledge discovery processes, and to translate knowledge from "bench to bedside" and "bedside to bench" with never-before efficiency. Filling the need for informatics applications that bridge the clinical-basic domains and facilitate the bi-directional flow of research, this definitive volume offers a systems-oriented approach to the subject that complements the traditional bottom-up approach of systems biology. You get clear insight into how to conduct biomedical informatics research at both the clinical and molecular levels, with detailed guidelines on study design, IRB protocol development, questionnaire design, specimen collection, and other procedures and applications. The book explains the latest data integration and federation approaches, and points the way to potential new data analysis and mining methodologies for tackling problems that cannot be readily resolved using current technologies. Complete with in-depth case examples demonstrating how to develop tools for specific biomedical informatics tasks, this pioneering work will prove invaluable to your efforts in managing clinical and high-throughput data and making the most of targeted basic research.