Microbiology and Immunology
Health Sciences Facility III, 670 West Baltimore St, Baltimore 21201
Education and Training
I received my Ph.D. from the University of Wisconsin-Madison in Computational Biology, specializing in 'omics' technologies. I pursued postdoctoral training in the Laboratory of Dr. Jacques Ravel and then joined the faculty at the Institute for Genome Sciences and Department of Microbiology and Immunology at the University of Maryland School of Medicine.
As a computational biologist, my research is at the forefront of the application of state-of-the-art ‘omics’ technologies to advance our understanding of the host-microbe ecosystem. Since graduate school, I have been embracing the evolving 'omics' technologies and the revolutionized transformation they brought to the research landscape. My career goal is to facilitate adapting the rapid advancements of innovative sequencing technologies into translatable mechanistic knowledge toward actionable prevention, diagnosis, and therapeutics.
Multi-‘Omics’, Big data, Genomics, Microbiome, Metagenomics, Metabolomics, Transcriptomics, Metatranscriptomics, single-cell RNA-seq, Microbe-Host Interaction, live biotherapeutics, Biomarker discovery, Data mining, GI Health, Systems Biology
- Ma B, Viscardi R, Ravel J, Composition and Methods for the Prediction of Necrotizing Enterocolitis (NEC) in Preterm Infants. US patent US20210254137
- Ravel J, France M, Rutt L, Ma B. Microbiome-based informed method to formulate live biotherapeutics. US Patent 11,037,655
- Ma B, et al. Ravel J. 2020. A comprehensive non-redundant gene catalog reveals extensive within-community intraspecies diversity in the human vagina. Nature communications. 11(1), 1-13
- Ma B*, et al. Viscardi R. 2022. Highly specialized carbohydrate metabolism capability in Bifidobacterium strain associated with intestinal barrier maturation in early preterm infants. mBio. 28;13(3):e0129922.
- France M., et al. Ma B., Forney, L.J., Ravel J. Insight into the ecology of vaginal bacteria through integrative analyses of metagenomic and metatranscriptomic data. Genome Biology. 23(1):66.
- France M, et al., Ma B., Ravel J. 2022. Towards a deeper understanding of the vaginal microbiota. Nature Microbiology 7 (3), 367-378