Bioinformatic Analysis of the Genetics of Common Complex Diseases

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Huge amounts of high-throughput sequencing data have been deposited in multiple public databases such as GEO and SRA. We use bioinformatic approaches to identify non-coding RNAs including circular (circ)RNAs associated with age-related cognitive decline and with Alzheimers Disease. We use bioinformatic approaches to analyze microbiome information in aging systems and age-related disease, especially the role of microbiome in Alzheimers Disease pathophysiology and progression. We also use various computational biology and machine learning approaches to analyze data regarding other complex human disease, aging, and age-associated disease processes. Over the years we have applied this effort to a number of projects including The Genetic Association Database, and genetic associations for Type 2 Diabetes, Alzheimer's disease, Obesity, Autism, and Autoimmune diseases.