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Teaming the Microbiome
Machine learning techniques have begun to revolutionize our understanding of how bacteria influence human and environmental health
If ever a match were made in scientific heaven, it’s between Big Data and Bioinformatics. Machine learning techniques have already begun to revolutionize our understanding of how bacteria influence human and environmental health and can efficiently produce a wide variety of products.
Getting biologists and statisticians to speak the same language, however, is not as straightforward. Funded by $3 million from the National Science Foundation, the Integrative Bioinformatics Graduate Training Program to Investigate and Engineer Microbiomes (IBIEM) promotes team science by bringing Duke and NC A&T University graduate students in engineering, microbiology, and other disciplines together to work on real-world projects and engage with local companies conducting microbiome-related research.
“All too often scientists only think about statistics at the end of an experiment, which can create issues for the data analysis and rigor in how good the experiment actually is,” said IBIEM director Claudia Gunsch of Duke CEE. “Having students and scientists that are able to communicate across these disciplines and think about the statistics from the start saves a lot of time in the long run and helps produce higher-quality data.”
Read more about IBIEM in coverage of the program's 2017 Symposium