The Biostatistics, Bioinformatics &Computational Biology Core (BBCB;Core E) will assist CFAR members with the management, analysis, modeling and annotation of complex and massive data generated by laboratory and clinical studies. The overall objective will be to provide a comprehensive solution that integrates expertise and resources in biostatistics, bioinformatics, computation, mathematical modeling and data management. Since its inception in 2010, Core E has developed and refined an innovative approach to optimally address investigator needs. This combines an integrated service model (""""""""one stop shopping"""""""") with an active and novel outreach strategy. Thus, rather than taking a traditional approach, in which requests for data analysis services are often initiated too late (after data are already generated, when one can no longer modify study design). Core E proactively engages with researchers. It does so by assigning core members to attend lab meetings (""""""""house calls"""""""") and to assist at the very earliest stages of study planning. Building on this innovative approach, five Aims are proposed.
Aim 1 will provide biostatistics support for experimental design and data analysis.
Aim 2 will provide bioinformatics and computational biology support, and will also promote interdisciplinary collaborations by supporting new applications of computationally-intensive methods to HIV/AIDS research (e.g., analyses of imaging data for our CNS Reservoirs/Aging SWG, and structural modeling for our RNA Biology SWG).
Aim 3 will provide data management and informatics services, and Aim 4 will provide education and training services. Finally, Aim 5 will leverage other available resources (including methodological research grants/projects and institutional support) to create novel statistical, computational, modeling and bioinformatics tools for HIV/AIDS research.
The Biostatistics, Bioinformatics &Computational Biology Core (BBCB;Core E) will assist CFAR members with the management, analysis, modeling and annotation of complex and massive data generated by laboratory and clinical studies.
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