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Apr
2
Tue
2024
Overcoming Analytic Challenges in Microbiome Science
Apr 2 @ 4:00 PM – 5:00 PM

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“Overcoming Analytic Challenges in Microbiome Science

UMIACS -Dr. Mihai Pop

Mihai Pop is a professor of computer science and director of the University of Maryland
Institute for Advanced Computer Studies. He develops computational approaches for analyzing
microbial communities, particularly for characterizing their strain-level diversity. Other
interests include biological databases, antibiotic resistance, and software testing. His lab
has developed several widely used open-source software tools for the analysis of genomic and
metagenomic data. Pop teaches at all academic professional levels, and is particularly
interested in developing open educational resources for introductory computer science and
bioinformatics. He strongly advocates for inclusion and diversity within the scientific
community. Pop completed his undergraduate studies in 1994 at the Politehnica University in
Bucharest, Romania, received his Ph.D. in computer science from Johns Hopkins University in 2000,
and has been at the University of Maryland since 2005. He is a fellow of the Association of
Computing Machinery and of the International Society for Computational Biology.

 

▶RECORDING [available here after event]

Abstract

“Overcoming Analytic Challenges in Microbiome Science

 

As microbiome research matures, it has become clear that a better understanding of the
microbial communities inhabiting our world is key to a better understanding of our
environment and of animal and human health. At the same time, we have become aware of
the limitations current microbiome technologies have, and of the tremendous challenges
posed by the analysis of the massive data sets generated in microbiome studies. In my
talk I will describe some of the research taking place in my lab aimed at developing
computational tools for microbiome analyses. I will specifically focus on challenges
related to the structure of biological databases, and the resulting impact on the
insights that can be derived from microbiome data.

 

▶RECORDING [available here after event]

JHU - Institute for Computational Medicine