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Title: Argonne News Brief: Cancer’s Big Data Problem

Abstract

Data is pouring into the hands of cancer researchers, thanks to improvements in imaging, models and understanding of genetics. But they’ll need a lot of help—and some powerful supercomputers—to translate this data into better, more personalized treatment for cancer patients. A new initiative called the Joint Design of Advanced Computing Solutions for Cancer, which taps four different national laboratories, is poised to help.

Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA); National Institutes of Health (NIH)
OSTI Identifier:
1334954
Resource Type:
Multimedia
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; ANL; JDACS4C; SUPERCOMPUTERS; CANCER; CANCER MOONSHOT; CANCER TREATMENT; CANCER DATA

Citation Formats

None. Argonne News Brief: Cancer’s Big Data Problem. United States: N. p., 2016. Web.
None. Argonne News Brief: Cancer’s Big Data Problem. United States.
None. Tue . "Argonne News Brief: Cancer’s Big Data Problem". United States. https://www.osti.gov/servlets/purl/1334954.
@article{osti_1334954,
title = {Argonne News Brief: Cancer’s Big Data Problem},
author = {None},
abstractNote = {Data is pouring into the hands of cancer researchers, thanks to improvements in imaging, models and understanding of genetics. But they’ll need a lot of help—and some powerful supercomputers—to translate this data into better, more personalized treatment for cancer patients. A new initiative called the Joint Design of Advanced Computing Solutions for Cancer, which taps four different national laboratories, is poised to help.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {11}
}

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