TY - JOUR
T1 - Harnessing big data for precision medicine
T2 - 22nd Pacific Symposium on Biocomputing, PSB 2017
AU - Yu, Kun Hsing
AU - Hart, Steven N.
AU - Goldfeder, Rachel
AU - Zhang, Qiangfeng Cliff
AU - Parker, Stephen C.J.
AU - Snyder, Michael
N1 - Funding Information:
K.-H. Y. is supported by a Howard Hughes Medical Institute (HHMI) International Student Research Fellowship and a Winston Chen Stanford Graduate Fellowship. R.G. is supported by a National Science Foundation (NSF) Graduate Research Fellowship. M.P. is partially supported by National Institutes of Health grants 1U54DE02378901, 5P50HG00773502, and 5U24CA16003605.
Publisher Copyright:
© 2017, World Scientific Publishing Co. Pte. Ltd. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Precision medicine is a health management approach that accounts for individual differences in genetic backgrounds and environmental exposures. With the recent advancements in high-throughput omics profiling technologies, collections of large study cohorts, and the developments of data mining algorithms, big data in biomedicine is expected to provide novel insights into health and disease states, which can be translated into personalized disease prevention and treatment plans. However, petabytes of biomedical data generated by multiple measurement modalities poses a significant challenge for data analysis, integration, storage, and result interpretation. In addition, patient privacy preservation, coordination between participating medical centers and data analysis working groups, as well as discrepancies in data sharing policies remain important topics of discussion. In this workshop, we invite experts in omics integration, biobank research, and data management to share their perspectives on leveraging big data to enable precision medicine.
AB - Precision medicine is a health management approach that accounts for individual differences in genetic backgrounds and environmental exposures. With the recent advancements in high-throughput omics profiling technologies, collections of large study cohorts, and the developments of data mining algorithms, big data in biomedicine is expected to provide novel insights into health and disease states, which can be translated into personalized disease prevention and treatment plans. However, petabytes of biomedical data generated by multiple measurement modalities poses a significant challenge for data analysis, integration, storage, and result interpretation. In addition, patient privacy preservation, coordination between participating medical centers and data analysis working groups, as well as discrepancies in data sharing policies remain important topics of discussion. In this workshop, we invite experts in omics integration, biobank research, and data management to share their perspectives on leveraging big data to enable precision medicine.
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U2 - 10.1142/9789813207813_0058
DO - 10.1142/9789813207813_0058
M3 - Conference article
C2 - 27897013
AN - SCOPUS:85015593580
SN - 2335-6936
VL - 0
SP - 635
EP - 639
JO - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
JF - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Y2 - 4 January 2017 through 8 January 2017
ER -