It’s our job to break down barriers, to access and to knowledge, and put big data and powerful methods in the hands of pediatric cancer experts poised for the next big discovery. Last month, the Childhood Cancer Data Lab’s (CCDL) peer-reviewed paper, MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease, was published by Cell Systems (Taroni et al. 2019.).
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We are a team of scientists, engineers, and designers developing products, services, and methods to empower the childhood cancer research community. We engineer systems using user-centered design approaches to ensure that computational methods reach a broader audience of researchers, amplifying the utility and impact of these approaches.
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