?BIOINFORMATICS GROUP The scale of research in the life sciences is increasing rapidly, due in part to the growing ubiquity of ?omics?. High-throughput and high-dimensional assay technologies, including variations of DNA sequencing, array/lab-on-a-chip assays, mass spectrometry, nuclear magnetic resonance spectroscopy, and other technologies, allow investigators to study entire genomes, transcriptomes, proteomes, metabolomes, microbiomes, and other large-scale systems. Researchers examine biological systems holistically, looking for patterns and emergent properties or simply cast a wide net by measuring many more variables simultaneously in an experiment. DAIT-funded investigators are increasingly using these approaches. Advances in information technology also drive the increasing scale of research by facilitating the creation, sharing, pooling, and analysis of large databases of research data. Bioinformatics meets these scalability opportunities and challenges by applying techniques from computing, statistics, mathematics, and engineering to the management, analysis, and dissemination of large and or complex biological data sets. The Bioinformatics Group (BG) will serve as a core component of the DAIT Statistical and Clinical Coordinating Center and will help maximize the value of data collected by DAIT-sponsored clinical and mechanistic investigators by fostering long-term capacity for data sharing and utilization by the general research community. Building on Rho's extensive experience as a Statistical and Clinical Coordinating Center for a number of NIH and DAIT research networks, the BG will play a role in every stage of the data lifecycle: During study planning the BG will provide expert guidance to investigators on experimental design, emerging technologies, and analytical approaches, particularly with regards to the application of omics and other high- dimensional data types. The team will collaborate with investigators and other bioinformatics organizations to develop data standards for clinical and mechanistic data and apply those to DAIT study data sets and information systems developed by the center. Implementing these standards will ensure that data are consistently structured and annotated and will make them more easily shared and pooled. The BG will provide tools, high performance computing infrastructure, and analytical support for high-throughput and high- dimensional data sets. Finally, it will serve as the primary conduit for data dissemination from supported DAIT programs through the development of study portals for live data access and transfer of final study data sets to public repositories, such as ImmPort and TrialShare.
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