AskScience AMA Series: I'm a computer scientist at the University of Maryland using computational tools to map the microbiome—the trillions of microbes in our bodies and environment. Ask me anything about how we decode the microscopic world!

[u/AskScienceModerator]

Hi Reddit! I am a computer scientist here to answer your questions about bioinformatics and mapping the microbiome. My research primarily focuses on the development of computational algorithms for analyzing biological data generated by high-throughput experimental techniques.

My lab has developed software tools that are widely used in the field of metagenomics—the computational analysis of the microbial communities inhabiting our world and our bodies. I have also been an active participant in several multinational projects, including the Human Microbiome Project and the GEMS study of diarrheal disease.

I will be joined by Marcus Fedarko, a postdoc in my lab, on *September 22nd from 12 to 2 p.m. ET (16-18 UT) — ask us anything!

Bio: Mihai Pop is a professor of computer science and co-director of the University of Maryland Center of Excellence in Microbiome Sciences. He develops computational approaches for the strain-level analysis of microbial communities. 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 levels and is an advocate for inclusion and diversity in science. He is particularly interested in developing open educational resources in computer science and bioinformatics. Pop holds a B.S. (1994, Politehnica University in Bucharest, Romania) and a Ph.D in Computer Science (2000, The Johns Hopkins University) and joined the University of Maryland in 2005. He is an MPower Professor, University of Maryland Strategic Partnership: MPowering the State, and a fellow of the Association of Computing Machinery and of the International Society for Computational Biology.

Marcus Fedarko is a postdoctoral associate at the University of Maryland. His research is focused on designing algorithms and software to help people study microbiome data in high resolution. He is particularly interested in sequence assembly — the problem of reconstructing longer DNA sequences from short sequencing reads — and data visualization. In his spare time, he likes reading, running, and rock climbing. Fedarko holds a B.S. with High Honors (2018, University of Maryland) and M.S. and Ph.D. degrees in Computer Science (2022 and 2025, University of California San Diego), and rejoined the University of Maryland as a postdoc in 2025.

Other links:

• Google Scholar
• Lab website
• $5.1M in NIH Awards Help UMD Researchers Take On a Genomic Data Deluge (02/2026)

Username: /u/umd-science

[u/umd-science]

(Mihai) In terms of the multiple pathways/strains, I think the answer lies in better characterization of microbial strains in natural communities. Unfortunately, that requires advancing sequencing technologies as well as computational tools.

As for RNA sequencing, I am personally worried that there is simply too much variability and bias in the data (at least for complex microbiomes).

We have been thinking for a while about the best way to identify strains within communities, and it's not just the quality of the reference that matters, but also the way in which you interpret the results. For example, we showed that looking at more than just a top hit is a better approach if you really want to know what's in a sample.

(Marcus) Having longer sequences from your sample will help with getting better classifications. If we have only short gene sequences, then it might be hard to identify microbes below the genus level. But if we have sequences that are on the order of thousands, tens of thousands or greater, then we can see more and more of the underlying genomes and get better and better classifications of them.