Scruggs Sarah B, Watson Karol, Su Andrew I, Hermjakob Henning, Yates John R, Lindsey Merry L, Ping Peipei
From the Departments of Physiology, Medicine, and Bioinformatics (S.B.S., P.P.) and Department of Medicine (K.W.), University of California, Los Angeles School of Medicine; Department of Molecular and Experimental Medicine (A.I.S.) and Departments of Chemical Physiology and Molecular and Cellular Neurobiology (J.R.Y.), The Scripps Research Institute, La Jolla, CA; Proteomics Services, European Molecular Biology Laboratories, European Bioinformatics Institute, Hinxton, Cambridge, United Kingdom (H.H.); and Departments of Physiology and Medicine, University of Mississippi Medical Center, Jackson (M.L.L.).
Circ Res. 2015 Mar 27;116(7):1115-9. doi: 10.1161/CIRCRESAHA.115.306013.
The exponential increase in Big Data generation combined with limited capitalization on the wealth of information embedded within Big Data have prompted us to revisit our scientific discovery paradigms. A successful transition into this digital era of medicine holds great promise for advancing fundamental knowledge in biology, innovating human health and driving personalized medicine, however, this will require a drastic shift of research culture in how we conceptualize science and use data. An e-transformation will require global adoption and synergism among computational science, biomedical research and clinical domains.
大数据生成的指数级增长，再加上对大数据中所蕴含信息财富的利用有限，促使我们重新审视科学发现范式。成功过渡到这个医学数字时代，有望推动生物学基础知识的进步、创新人类健康并推动个性化医疗，然而，这将需要在我们如何概念化科学和使用数据方面对研究文化进行彻底转变。电子转型将需要计算科学、生物医学研究和临床领域的全球采用与协同合作。
