BIOINFORMATICS

Johns Hopkins University, Baltimore MD

Investigators

Linked publications, trials & patents

Abstract

The mission of the Bioinformatics Shared Resource (BISR) is to guarantee the availability of comprehensive bioinformatics expertise to Sidney Kimmel Comprehensive Cancer Center (SKCCC) members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR achieves this by partially funding the effort for several PhD-level investigators and related staff. BISR faculty have extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems. A critical development during the next funding period will be the emergence of large data sets comprising multiple omics data, including genomics (SNPs, allelic variation maps from high-throughput sequencing), epigenomics (methylation an-ays, bi-sulfite high-throughput sequencing), transcriptomics (microarrays and RNA-seq), proteomics (MS-MS and arrays), and metabolomics (MS and NMR). These data will require integration through annotations, both through genome sequence and using proteomic-based integration. Computational modeling of this data will play an increasingly important role, as the data could overwhelm mathematical analysis approaches that lack a biologically motivated model to place the data in context Pathway, network, and cellular systems analysis is expected to play a growing role in data interpretation, with systems biology and computational modeling emerging as critical capabilities for the BISR. This Core has been assembled with the breadth in expertise necessary for these developments. Lay: The Bioinformatics Resource provides comprehensive bioinformatics expertise to Cancer Center members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR has several PhD-level investigators with extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems, together with support staff.