Assistant Professor Farzana Nasrin has collaborated with the School of Life Sciences in a project to investigate genetic and metabolic components that may be related to repetitive behaviors that are common in people with autism. Their project received a five-year, $1.5M R01 National Institutes of Health/National Institute of General Medical Sciences grant.

This project will analyze complex sets of data (20,000 genes, 300 serum metabolites, and 1,000 gut microorganisms, as well as 3D-imaging of active neurons in fish brains). The team assumes that it is fair to use the fish project to predict the possible genetic and molecular pathways because humans and fish share more than 90% of gene and molecular pathways. These high dimensional data sets are challenging to visualize and analyze. However, by integrating topological mapping and statistical machine learning algorithms, the researchers are developing effective and flexible methods to analyze them with a limited amount of training samples.

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