Jennifer J. Barb, PhD, MS

BS, University of Maryland, Baltimore County
MS, Johns Hopkins University
PhD, George Mason University

Dr. Barb has been a data analytics and bioinformatics scientist at the NIH for over 20 years where she began her career in the Mathematical and Statistical Computing Laboratory (MSCL) at the Center for Information Technology in 2001. Dr. Barb has two Bachelor of Science degrees in the Biological Sciences and in Computer and Information Science. Dr. Barb has a MS in Biotechnology with a concentration in Bioinformatics and a PhD in Bioinformatics.

She transferred from CIT to the Clinical Center in 2019 to work with PI Dr. Gwenyth Wallen.

Dr. Barb’s research interest focuses on three main areas: 1) high-throughput data analysis in disease specific genomics, 2) microbiome methods and applications on human clinical data and specifically of health disparities and 3) data discovery methods applied to specific diseases. Dr. Barb also has a special interest in nutrition and its association with the gut microbiome.

Throughout her career at the NIH, she has served as a collaborator on over 50 projects and has collaborated with NIAAA, NCI, NHLBI, NEI, NHGRI, NINR, NIDCR, NICHD, NIMH, NIAID, NINDS, Forsyth Institute and the Framingham Heart Study.

She has coauthored many peer-reviewed publications and has presented her work in poster and oral formats at various conferences. She has worked extensively on the development of genomic analytical methods and developed a statistical Toolbox for high throughput data analysis for gene expression microarrays. She has experience in a large range of bioinformatics analysis methods and clinical data analysis. She takes a hands-on approach to not only address the main questions of her research but also allows the data to drive the discovery.

Current Research Activities

Associate Investigator

17-DA-0093 (NCT# 03152760): Gut-Brain and Brain-Gut Interactions in Alcohol Use Disorder via Microbiota Investigations: A Pilot Study (NIDA, PI: Lorenzo Leggio)

000871-CC (NCT# 05411120): Mediterranean-like Unprocessed (CLEAN-MED) Diet Intervention Study of the Gut Microbiome of Healthy Adults (CC, PI: Karen Frank)

MODCR000708 (NCT# 01148381): Characterization of Phenotypic and Genotypic Regressors (NIDA, PI: Betty Jo Salmeron)

22-DK-0002 (NCT05290064): Effects of Ultra-processed versus Unprocessed Diets on Energy Metabolism (NIDDK, PI: Kevin Hall)

(NCT06044935): Effect of Nicotinamide Riboside on Ketosis, Fat Oxidation & Metabolic Rate (NIDDK, PI: Kevin Hall)

000796: Associations between Cytokine and Metabolite-Associated Gut Microbiome Bacteria, Structural Magnetic Resonance Imaging Features and Clinical Phenotype (craving, anxiety, and depression) in patients with Alcohol Use Disorder (PI: Dr. Gwenyth Wallen)

16-CC-0162 (NCT# 02911077): Longitudinal changes in the oral and gut microbiome of individuals with alcohol dependence (PI: Dr. Gwenyth Wallen)

14-CC-0143 (NCT# 02181569): Sleep disturbance and relapse in individuals with alcohol dependence: an exploratory mixed methods study (PI: Dr. Gwenyth Wallen)

• Highlight in the NIAAA/NIH Spectrum, 2020
• Center for Information Technology Scientific Award of Merit, 2017
• National Institutes of Health Clinical Center Director’s Award, 2016
• C.W. Cotterman Award, (Sen et. al, co-author on publication), 2014
• American Society of Human Genetics for publication in AJHG
• Awarded Best Student’s Poster Award JMP User’s Conference, SAS Headquarters, Cary, NC, 2008

Valencia EM, Maki KA, Dootz JN, & Barb JJ (2024). Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines. Scientific data, 11(1), 81. https://doi.org/10.1038/s41597-023-02877-7

Farmer N, Maki KA, Barb JJ, Jones KK, Yang L, Baumer Y, Powell-Wiley TM, & Wallen GR (2023). Geographic social vulnerability is associated with the alpha diversity of the human microbiome. mSystems, 8(5), e0130822. https://doi.org/10.1128/msystems.01308-22

Barb JJ, Brooks AT, Kazmi N, Yang L, Chakravorty, S, Wallen GW. A lower sleep regularity index is associated with relapse in individuals with alcohol use disorder following inpatient treatment. 2022. Nature Scientific Reports, in press.

Kazmi N, Wallen GW, Yang L, Alkhatib J, Schwandt M, Feng D, Gao B, Diazgranados N, Ramchandani V*, Barb JJ* 2022. An exploratory study of pro-inflammatory cytokines in individuals with Alcohol Use Disorder: MCP-1 and IL-8 associated with alcohol consumption, sleep quality, anxiety, depression, and liver biomarkers. (*co-senior author), Frontiers in Psychiatry: Section Addiction Disorders. PMID: 36032219 PMCID: PMC9405018

Yang S, Ratteree K, Turner SA, Tuason RT, Brooks A, Wallen GR, Barb JJ Dietary Intakes of Patients with Alcohol Use Disorder During a 4-Week Protocol on an Inpatient Treatment Unit Found to Meet Dietary Reference Intakes for Macronutrients, but Have Variability in Energy Balance and Adequacy of Micronutrient Intake. J Acad Nutr Diet. 2022 Jun 2:S2212-2672(22)00316-1. PMID: 35659642.

Meeks BK, Maki KA, Ames NJ, & Barb JJ (2022). Comparing Published Gut Microbiome Taxonomic Data Across Multinational Studies. Nursing research, 71(1), 43–53.

Barb JJ, Maki KA, Kazmi N, Meeks BK, Krumlauf M, Tuason RT, Brooks AT, Ames NJ, Goldman D, & Wallen GR (2021). The oral microbiome in alcohol use disorder: a longitudinal analysis during inpatient treatment. Journal of oral microbiology, 14(1), 2004790.

Maki KA, Kazmi N, Barb JJ, & Ames N. The Oral and Gut Bacterial Microbiomes: Similarities, Differences, and Connections. Biological research for nursing. 2021. https://doi.org/10.1177/1099800420941606

Ames NJ*, Barb JJ*, Schuebel K, Mudra S, Meeks BK, Tuason R, Brooks AT, Kazmi N, Yang S, Ratteree K, Diazgranados N, Krumlauf M, Wallen GR, & Goldman D. Longitudinal gut microbiome changes in alcohol use disorder are influenced by abstinence and drinking quantity. Gut microbes. 2020; 11(6), 1608–1631. (*co-first author), https://doi.org/10.1080/19490976.2020.1758010

Barb JJ, Oler AJ, Kim HS, Chalmers N, Wallen GR, Cashion A, Munson PJ, & Ames NJ. Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples. PloS one. 2016;11(2), e0148047. https://doi.org/10.1371/journal.pone.0148047

Raghavachari N, Barb J, Yang Y, Liu P, Woodhouse K, Levy D, O'Donnell CJ, Munson PJ, & Kato GJ. A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease. BMC medical genomics. 2012; 5, 28. https://doi.org/10.1186/1755-8794-5-28

Visit Scopus or ResearchGate for a full list of Dr. Barb's publications.