Resource Labs

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Center for Computational Discovery

The Center for Computational Discovery (CCD) uses computational, bioinformatic, and statistical approaches to analyze complex biological datasets for basic discovery, translational, and clinical research.

OverviewA major challenge in modern cancer research is the generation, storage, analysis, and interpretation of complex experimental data. Individual experiments using cutting-edge technologies can generate terabytes of data that must be quantitatively mined to identify important cancer genes, pathways, and drug associations, to drive the discovery of new biomarkers and drug targets. CCD scientists have significant expertise in the analysis of high-throughput biological data from across the current technological spectrum including next-generation sequencing (DNA, RNA, ChIP-seq), microarrays (e.g. SNP, CHG, Expression, Tiling, ChIP-Chip), proteomics (array-based), genome-scale RNAi and chemical screens, and high-throughput microscopy. Scientists in the Center are developing new methods for the analysis, display, and storage of large data sets generated with these cutting edge technologies. CCD scientists also work closely with a wide-spectrum of investigators throughout the Cancer Center on a variety of translational and fundamental research projects at any given time, both as collaborators and consultants. In approaching new projects, we are able to apply established analytic tools and also develop, implement, and deploy customized tools depending on specific requirements. Current projects involve cancer genomic discovery, pharmacogenomics, epigenomics, meta-analysis, data integration, and predictive modeling.

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