The Bioinformatics Core is an important component ofthe Michigan O'Brien Kidney Translational Core Center. This core will provide access to computational applications and skilled professional support in bioinformatics and biostatistics Increasingly large and complex data sets require computational support for analyses, and the presence of this core will enhance the research. The Bioinformatics Core will provide analytical support for large datasets including microarray, and next generations sequencing applications for genomics, transcriptomics, proteomics and epigenetics. The Bioinformatics Core is aligned to the overall goals ofthe Center and will provide focused, specific support for researchers studying chronic kidney disease. To be successful, this core will provide guidance and assistance to Center researchers at all stages of research from experimental design to data generation and analysis of molecular profiling data. The Bioinformatics Core will be fully integrated with the DNA sequencing core for smooth coordination of data transfer and analysis. The system's biology core will also be integrated with the Bioinformatics Core to provide deeper analysis ofthe project data and combine the different molecular profiling analyses.
Bioinformatics and biostatistics are essential for the analysis and interpretation of large data sets. The inclusion of this core to the Michigan O'Brien center is crucial to providing complete support for chronic kidney disease researchers.
|Yu, Haiyang; Artomov, Mykyta; BrÃ¤hler, Sebastian et al. (2016) A role for genetic susceptibility in sporadic focal segmental glomerulosclerosis. J Clin Invest 126:1603|
|Venkatareddy, Madhusudan; Verma, Rakesh; Kalinowski, Anne et al. (2016) Distinct Requirements for Vacuolar Protein Sorting 34 Downstream Effector Phosphatidylinositol 3-Phosphate 5-Kinase in Podocytes Versus Proximal Tubular Cells. J Am Soc Nephrol 27:2702-19|
|Sas, Kelli M; Kayampilly, Pradeep; Byun, Jaeman et al. (2016) Tissue-specific metabolic reprogramming drives nutrient flux in diabetic complications. JCI Insight 1:e86976|
|Sampson, Matthew G; Robertson, Catherine C; Martini, Sebastian et al. (2016) Integrative Genomics Identifies Novel Associations with APOL1 Risk Genotypes in Black NEPTUNE Subjects. J Am Soc Nephrol 27:814-23|
|Brosius, Frank C; Tuttle, Katherine R; Kretzler, Matthias (2016) JAK inhibition in the treatment of diabetic kidney disease. Diabetologia 59:1624-7|
|Yao, Yao; Wang, Junying; Yoshida, Sei et al. (2016) Role of Ragulator in the Regulation of Mechanistic Target of Rapamycin Signaling in Podocytes and Glomerular Function. J Am Soc Nephrol 27:3653-3665|
|Naik, Abhijit S; Afshinnia, Farsad; Cibrik, Diane et al. (2016) Quantitative podocyte parameters predict human native kidney and allograft half-lives. JCI Insight 1:|
|Betz, Boris; Conway, Bryan R (2016) An Update on the Use of Animal Models in Diabetic Nephropathy Research. Curr Diab Rep 16:18|
|Hur, Junguk; O'Brien, Phillipe D; Nair, Viji et al. (2016) Transcriptional networks of murine diabetic peripheral neuropathy and nephropathy: common and distinct gene expression patterns. Diabetologia 59:1297-306|
|Saito, Rintaro; Rocanin-Arjo, AnaÃ¯s; You, Young-Hyun et al. (2016) Systems biology analysis reveals role of MDM2 in diabetic nephropathy. JCI Insight 1:e87877|
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