Under the leadership of Dr. Mark Knepper and the steering committee, the DIR Systems Biology Core continue to provided a wide range of services, to facilitate basic and transformative research at NHLBI and across the NIH, utilizing not only bioinformatics and biostatistics, but also techniques and concepts from graph theory, mathematics and physics. core has provided consultation service in study design in terms of sample size and power calculations, design of control experiments, maximization of the information that can be obtained, tools and databases that can be utilize for data mining, as well as mathematical technique for modeling. (2) In-depth data analysis and modeling: The Core has implemented a wide range of open source and commercially available software packages, as well in house developed software and database, for primary and secondary analysis of NGS and proteomics data, data integration, pathway and network enrichment analysis, bioinformatics data mining, and mathematical modeling. These enable DIR investigators to identify the patterns in their data, biological theme in the patterns, model the underlying principles of the patterns and themes observed, formulate new hypothesis, new questions, and design new experiments (3) Education and training: The Core has taken several efforts to promote awareness and appreciations of concepts and techniques in systems biology, including but not limited to: a weekly journal club where core members take turn to present the most recent articles in the top bioinformatics and systems biology journals; a workstation that is available to DIR staff to come and utilize and software and hardware resources, and to work side-by-side with a core staff member. (4) Research and development: Several R&D projects has been carried out in collaboration with the DIR investigators, prioritized based the mission of the DIR and the popular interests of the DIR investigators. This include new means to analyze pseudo-time ordered single cell genomics data, integration of miRNA-seq and mRNA-seq data, deconvolution of tissue functional genomics data to cell types, and off-target analysis of CRISPR data.
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