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17 April 2013
Vol 5, Issue 181

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ONLINE COVER "Doin' It for Themselves"—and Future Generations. A U.S. cultural icon, Rosie the Riveter represents millions of American women who entered the workforce during World War II. Rosies worked in factories of all kinds, including some that manufactured munitions and other supplies needed for the war effort. In the realm of biomedical research, women from around the world are now supplying ammunition—their clinical and genomic data—for a war of another kind: the one against breast cancer. In a recent crowdsourced research competition—the Sage Bionetworks–DREAM Breast Cancer Prognosis Challenge—participants made use of gene expression, gene copy number, and clinical data, obtained from breast cancer samples from more that 2000 women, to develop prognostic models for breast cancer survival in an open challenge environment. In this week’s issue, a Report by Margolin et al. describes the Challenge’s conception and execution as well as insights derived from its outcome. In a companion Research Article, Cheng et al. outline the development of the prognostic computational model that won the Challenge. [CREDIT: ADAPTED FROM J. HOWARD MILLER/WESTINGHOUSE]

About The Cover

Cover image expansion

ONLINE COVER "Doin' It for Themselves"—and Future Generations. A U.S. cultural icon, Rosie the Riveter represents millions of American women who entered the workforce during World War II. Rosies worked in factories of all kinds, including some that manufactured munitions and other supplies needed for the war effort. In the realm of biomedical research, women from around the world are now supplying ammunition—their clinical and genomic data—for a war of another kind: the one against breast cancer. In a recent crowdsourced research competition—the Sage Bionetworks–DREAM Breast Cancer Prognosis Challenge—participants made use of gene expression, gene copy number, and clinical data, obtained from breast cancer samples from more that 2000 women, to develop prognostic models for breast cancer survival in an open challenge environment. In this week’s issue, a Report by Margolin et al. describes the Challenge’s conception and execution as well as insights derived from its outcome. In a companion Research Article, Cheng et al. outline the development of the prognostic computational model that won the Challenge. [CREDIT: ADAPTED FROM J. HOWARD MILLER/WESTINGHOUSE]