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BIOINFORMATICS

$250,908P30FY2010CANIH

Johns Hopkins University, Baltimore MD

Investigators

Linked publications, trials & patents

Trial NCT02989636Trial NCT02516670Trial NCT02491411Trial NCT02489357Trial NCT02029950Trial NCT01935947Trial NCT01870596Trial NCT01783171Trial NCT01757639Trial NCT01578109Trial NCT01349972Trial NCT01349959Trial NCT01330173Trial NCT01264432Trial NCT01207726Trial NCT01207687Trial NCT01139970Trial NCT01132573Trial NCT01061749Trial NCT00971737Trial NCT00963807Trial NCT00899951Trial NCT00899548Trial NCT00898482Trial NCT00897338Trial NCT00897273Trial NCT00847171Trial NCT00795002Trial NCT00727441Trial NCT00673569Trial NCT00670917Trial NCT00660348Trial NCT00641303Trial NCT00641147Trial NCT00631137Trial NCT00616967Trial NCT00602771Trial NCT00588991Trial NCT00566098Trial NCT00524017Trial NCT00499733Trial NCT00499486Trial NCT00493025Trial NCT00492921Trial NCT00489281Trial NCT00478062Trial NCT00478010Trial NCT00471653Trial NCT00470093Trial NCT00469820Trial NCT00445484Trial NCT00433472Trial NCT00425477Trial NCT00407966Trial NCT00401024Trial NCT00389610Trial NCT00387465Trial NCT00381550Trial NCT00373191Trial NCT00369681Trial NCT00368914Trial NCT00363649Trial NCT00361296Trial NCT00356928Trial NCT00354640Trial NCT00343447Trial NCT00336063Trial NCT00334542Trial NCT00324870Trial NCT00313560Trial NCT00311623Trial NCT00305760Trial NCT00303927Trial NCT00293410Trial NCT00293397Trial NCT00293280Trial NCT00290732Trial NCT00287989Trial NCT00287872Trial NCT00281970Trial NCT00281866Trial NCT00278200Trial NCT00278161Trial NCT00278109Trial NCT00276744Trial NCT00276601Trial NCT00276588Trial NCT00274768Trial NCT00265915Trial NCT00265837Trial NCT00262834Trial NCT00258206Trial NCT00258180Trial NCT00255775Trial NCT00255710Trial NCT00245115Trial NCT00244959Trial NCT00242996Trial NCT00238368Trial NCT00238277

Abstract

The last decade has seen a substantial growth in the use of high-throughput molecular technologies in cancer research across the SKCCC. Efficient utilization of the data generated by these experiments is of strategic scientific importance and requires bioinformatics support. The bioinformatics shared resource guarantees the availability of comprehensive bioinformatics expertise to Cancer Center members. This resource comprises faculty and support staff able to support data acquisition (including study design, feasibility of objectives, availability of public-access genomic information, data storage, and data annotation), statistical quality control (including artifact detection, preprocessing, and normalization of data from genomic technologies), data analysis (including visualization, modeling, inference and interpretation), and development of innovative customized bioinformatics tools, and education. This resource stabilizes and expands existing high-quality expertise in the areas of computational molecular biology, bioinformatics, and computing-intensive statistical genetics. Organizing this expertise as a Shared Resource is a costeffective approach to ensure that qualified bioinformatics support is readily available to investigators from all programs in the center. Resource members are in an ideal position to initiate and promote interdisciplinary interactions among cancer research projects led by different investigators, and thus speed the bi-directional exchange between basic and clinical science. Members of the Shared resource will also continue to develop their own agenda of cancer bioinformatics research, to participate in educational activities in the Cancer Center and across the University, and to be active in the profession. These dimensions will be funded separately from this submission, but are critical in the development of a group able to provide Cancer Center investigators with reliable, state-of-the-art, and broad-based expertise.

View original record on NIH RePORTER →