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
. Argonne News Brief: Cancer’s Big Data Problem. United States: N. p., 2016.
Web.
. Argonne News Brief: Cancer’s Big Data Problem. United States.
. 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 = {},
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 = {Tue Nov 29 00:00:00 EST 2016},
month = {Tue Nov 29 00:00:00 EST 2016}
}