Computational Biomarker Discovery in the Human Microbiome
ABSTRACT: The human body is home to trillions of microbes, collectively called the microbiome, which play important roles in many major human diseases including obesity, diabetes, inflammatory bowel disease, and certain forms of cancer. However, microbiomes are large and complex, requiring analysis of massive quantities of microbial DNA from biological samples, and the lack of precise methods for analyzing microbiomes is limiting progress in identifying specific disease modulatory mechanisms in microbiome research. This talk describes several new algorithms and software tools that enable new types of biomarker discovery in microbiome data, and then demonstrates application of these tools to clinically relevant human and primate studies.
BIO: Dr. Dan Knights is a computational microbiologist. He is an assistant professor in the Department of Computer Science and Engineering and the Biotechnology Institute at the University of Minnesota. Dan received his B.A. from Middlebury College, and his PhD from the University of Colorado, both in Computer Science, followed by a post-doctoral fellowship at Harvard. His research uses data mining and machine learning to aggregate and mine multiple sources of microbial and human genomic data for patterns linking to environmental conditions and human disease. Dan has co-authored articles in top multidisciplinary journals, including 6 publications in Nature, Science and Cell. In 2015 he was named a McKnight Land-Grant Professor by the University of Minnesota. He has been the expert witness on National Public Radio's "Wait Wait...Don't Tell Me!", and was the official 2003 Rubik's Cube World Champion. He was also the first person in the world to solve Rubik's Cube blindfolded.