Bioinformatics and Modeling Core
- Institution
- CINCINNATI CHILDRENS HOSP MED CTR, OH
- Principal investigator
- Matthew Tyson Weirauch
- Funding
- $137K
- Duration
- 2016–2028
Moonbase score
Still being scored
Abstract
Project Summary/Abstract – Bioinformatics and Modeling (BAM) Core Rheumatic diseases adversely affect the lives of millions of Americans. Yet, modern therapies remain largely ineffective. Detailed knowledge of molecular disease mechanisms transforms medical management, therapeutic approaches, diagnostics, and preventive strategies. Advances in bioinformatic and modeling approaches have been, and will continue to be, tantamount to revealing rheumatic disease mechanisms. The goal of the Bioinformatics and Modeling (BAM) Core is to drive the quality control, analysis, integration, modeling, and dissemination of large datasets to understand inflammatory and rheumatic diseases. To this end, the BAM Core will continue to offer unique computational services and expertise to the P30 research community, the Cincinnati Children’s Hospital Medical Center and University of Cincinnati research community, and collaborators at other institutions. The BAM Core will implement innovative genomics and immunophenotyping data management and analytic strategies to interrogate the datasets generated by users of the Cincinnati Rheumatic Disease Resource Center. Publicly available software packages and newly developed, innovative tools will be integrated, automated, applied and made available to the larger research community. The following Specific Aims will be spearheaded by The BAM Core in close collaboration with the Research Base investigators and the Functional Genomics, Integrative Cell Phenotyping, and Tissue Repository Cores: Aim 1. To provide analytic expertise and informatic support for functional genomic experiments. Aim 2. To support genotype-dependent analysis of functional genomic experiments. Aim 3. To analyze high-dimensional flow cytometry data. Aim 4. To facilitate the organization and deposition of genetic, genomic, and proteomic data.
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