Anthony Fodor - Professor
Anthony Fodor’s lab focuses on the application of analytical techniques to the enormous data sets of modern biology. In addition to participating in numerous studies that have linked the state of the human microbial community to health and disease, he was a member of the data analysis team analyzing 16S rRNA data generated from the Human Microbiome Project and, more recently, the Microbiome Quality Control Project. His research interests include algorithm development and pipeline automation in the service of establishing robust techniques for reproducible meta-analyses. He holds a Ph.D. in Physiology and Biophysics from the University of Washington. He is a Professor in the Department of Bioinformatics and Genomics at the University of North Carolina at Charlotte, where he has been since 2005.
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Malcolm is interested in reproducibility in human gut microbiome experiments. Lately he has been obsessed with containerizing applications and workflows using Docker and Amazon Web Services.
Favorite Languages: BASH, Python, R
Favorite bacteria: Lactobacillus bulgaricus, due to its involvement in yogurt and Thermus aquaticus because it was discovered surviving and thriving where nobody thought possible.
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Farnaz's research is focused on analyzing microbiome data generated from high-throughput next generation sequencing to study how the microbiome affects human health. She is interested in the application of statistical models and new algorithms in metagenomics. Farnaz earned her PharmD at Shahid Beheshti University in Iran and her PhD in Pharmaceutical Sciences at North Dakota State University, where she studied the relationship between the gut microbiome, bile acids, and gut peptides and their effects on weight outcomes following bariatric surgery. In her free time, Farnaz enjoys hiking, reading, and spending time with friends.
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Shan's research focuses on exploring the relationships between microbiota and human health in multiple large-scale cohorts by mining amplicon sequencing, metagenome sequencing and RNA-Seq data with classic statistical models and machine learning approaches. She is also interested in the development of analytical techniques for meta-analysis. She completed her PhD training in environmental microbiology at Virginia Tech and moved to UNC Charlotte for more training in biostatistics and bioinformatics approaches for large sequencing datasets. In her spare time, she enjoys hiking, vegetable gardening and entertaining her two dogs.
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