Mayetri Gupta, PhD
Adjunct Associate Professor
Boston University School of Public Health
Dept of Biostatistics

PhD, Harvard University
MS, Indian Statistical Institute



Dr. Gupta's research focus is at the interface of Statistics and Computational Biology, addressing high-dimensional and missing data problems in genomics and bioinformatics, especially relating to gene regulation. Her methodological work includes the development of several novel statistical methods for the discovery of transcription factor binding sites from DNA sequence in a variety of genomes, ranging from bacteria to human.She has been extensively involved in the development of Bayesian methodologies for the discovery of gene regulatory networks combining multiple genomic data types, and discovery and analysis of chromatin features from high throughput data from genome tiling arrays. More recently, she has been involved in developing Bayesian methods for analysis of data from genome-wide association studies, and next generation sequencing data. Her other statistical research interests include Bayesian model and variable selection, Bayesian methods for clustering and classification and inference in hidden Markov and other latent class models. For more information about Dr.Gupta's work, please visit http://people.bu.edu/gupta/. Dr. Gupta also serves as a Bioinformatics mentor for the Biostatistics Training Grant in the department of Biostatistics.


Bayesian Approaches to Model Selection for Survival Data
09/15/2011 - 08/31/2012 (PI)
University of North Carolina at Chapel H NIH NIGMS
2 R01 GM070335 13A1



Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

  1. Moser CB, Gupta M, Archer BN, White LF. The impact of prior information on estimates of disease transmissibility using Bayesian tools. PLoS One. 2015; 10(3):e0118762.View Related Profiles. PMID: 25793993; PMCID: PMC4368801; DOI: 10.1371/journal.pone.0118762;.
  2. Bis JC, DeStefano A, Liu X, Brody JA, Choi SH, Verhaaren BF, Debette S, Ikram MA, Shahar E, Butler KR, Gottesman RF, Muzny D, Kovar CL, Psaty BM, Hofman A, Lumley T, Gupta M, Wolf PA, van Duijn C, Gibbs RA, Mosley TH, Longstreth WT, Boerwinkle E, Seshadri S, Fornage M. Associations of NINJ2 sequence variants with incident ischemic stroke in the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium. PLoS One. 2014; 9(6):e99798.View Related Profiles. PMID: 24959832; PMCID: PMC4069013; DOI: 10.1371/journal.pone.0099798;.
  3. Lin H, Wang M, Brody JA, Bis JC, Dupuis J, Lumley T, McKnight B, Rice KM, Sitlani CM, Reid JG, Bressler J, Liu X, Davis BC, Johnson AD, O''Donnell CJ, Kovar CL, Dinh H, Wu Y, Newsham I, Chen H, Broka A, DeStefano AL, Gupta M, Lunetta KL, Liu CT, White CC, Xing C, Zhou Y, Benjamin EJ, Schnabel RB, Heckbert SR, Psaty BM, Muzny DM, Cupples LA, Morrison AC, Boerwinkle E. Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. Circ Cardiovasc Genet. 2014 Jun; 7(3):335-43.View Related Profiles. PMID: 24951659; PMCID: PMC4176824; DOI: 10.1161/CIRCGENETICS.113.000350;.
  4. Lin H, Sinner MF, Brody JA, Arking DE, Lunetta KL, Rienstra M, Lubitz SA, Magnani JW, Sotoodehnia N, McKnight B, McManus DD, Boerwinkle E, Psaty BM, Rotter JI, Bis JC, Gibbs RA, Muzny D, Kovar CL, Morrison AC, Gupta M, Folsom AR, Kääb S, Heckbert SR, Alonso A, Ellinor PT, Benjamin EJ. Targeted sequencing in candidate genes for atrial fibrillation: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study. Heart Rhythm. 2014 Mar; 11(3):452-7.View Related Profiles. PMID: 24239840; PMCID: PMC3943920; DOI: 10.1016/j.hrthm.2013.11.012;.
  5. Gelfond JA, Ibrahim JG, Gupta M, Chen MH, Cody JD. Differential expression analysis with global network adjustment. BMC Bioinformatics. 2013; 14:258. PMID: 23968143; PMCID: PMC3766173; DOI: 10.1186/1471-2105-14-258;.
  6. Hendricks AE, Dupuis J, Gupta M, Logue MW, Lunetta KL. A comparison of gene region simulation methods. PLoS One. 2012; 7(7):e40925.View Related Profiles. PMID: 22815869; PMCID: PMC3399793; DOI: 10.1371/journal.pone.0040925;.
  7. Moser C, Gupta M. A generalized hidden Markov model for determining sequence-based predictors of nucleosome positioning. Stat Appl Genet Mol Biol. 2012; 11(2). PMID: 22499697; DOI: 10.2202/1544-6115.1707;.
  8. Gupta M, Cheung CL, Hsu YH, Demissie S, Cupples LA, Kiel DP, Karasik D. Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associations. J Bone Miner Res. 2011 Jun; 26(6):1261-71.View Related Profiles. PMID: 21611967; PMCID: PMC3312758; DOI: 10.1002/jbmr.333;.
  9. Mitra R, Gupta M. A continuous-index Bayesian hidden Markov model for prediction of nucleosome positioning in genomic DNA. Biostatistics. 2011 Jul; 12(3):462-77. PMID: 21193724; PMCID: PMC3114652; DOI: 10.1093/biostatistics/kxq077;.
  10. Meltzer M, Long K, Nie Y, Gupta M, Yang J, Montano M. The RNA editor gene ADAR1 is induced in myoblasts by inflammatory ligands and buffers stress response. Clin Transl Sci. 2010 Jun; 3(3):73-80.View Related Profiles. PMID: 20590675; PMCID: PMC2897727; DOI: 10.1111/j.1752-8062.2010.00199.x;.
Showing 10 of 20 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 20 publications over 11 distinct years, with a maximum of 4 publications in 2009

YearPublications
20051
20061
20073
20081
20094
20102
20111
20122
20132
20142
20151
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