Munni Begum

Munni Begum

Professor of Mathematical Sciences


Room:RB 431


B.S. in Statistics, University of Dhaka, Dhaka 1994
M.S. in Statistics, University of Dhaka, Dhaka, 1996
M.A. in Statistics, Ball State University, Indiana, 2001
Ph.D. in Biostatistics, University of North Carolina at Chapel Hill, 2005

Research Interests:

  • Methods and principles of Statistics and Biostatistics
  • Statistical Learning and Predictive modeling
  • Statistical Computing in Bioinformatics and Molecular Biology
  • Linear and generalized linear modeling
  • Time dependent and longitudinal data analysis
  • Multivariate techniques
  • Survival Analysis
  • Bayesian methods and hierarchical modeling

Selected Publications

  • Tasnia Ahmed and Munni Begum (2018). Association between Gene Expression, Clinical
    Factors and Survival in Patients with Breast Cancer. Journal of Biomedical Analytics. Vol1(1): 1-14.
  • Farhin Rahman and Munni Begum (2017). Survival Analysis of Recurrent Events on
    Prostate Cancer : Facts from Cancer Genome. Journal of Statistical Research. Vol(51)(2):145-164.
  • Alexander H.K. Montoye, Munni Begum, Zachary Henning, and Karin A. Pfeiffer (2017).
    Comparison of linear and non-linear models for predicting energy expenditure from raw
    accelerometer data. Physiological Measurement. Vol 38(2).
  • Naim Al Mahi and Munni Begum (2016). A two step integrated approach to detect
    differentially expressed genes in RNA-Seq data. Journal of Bioinformatics and
    computational Biology
    Vol 14(6),
  • Munni Begum, John Horowitz, and Naim Al Mahi (2016). Cancer risk from exposure to low
    to moderate level of arsenic using meta-analysis of flexible regression models. Biometrics
    and Biostatistics International Journal,
    Vol 3(3).
  • Munni Begum, Avshek Mallick and Nabendu Pal (2014), A Generalized Inflated Poisson
    Distribution with Application to Modeling Fertility Data, Thailand Statistician 12(2): 135 -
  • Munni Begum, Jay Bagga, Ann Blakey and Sudipta Saha (2014). Network motif
    identification and structure detection with graphical models, Network Biology 4(4):
  • Munni Begum, John Horowitz, and Md. Irfan Hossain (2012). Low-Dose Risk Assessment
    for Arsenic: A Meta-Analysis Approach. Asia Pac J Public Health 1010539512466568,
  • Munni Begum, Jay Bagga, and Ann Blakey (2012). Graphical Modeling for High
    Dimensional Data, Journal of Modern Applied Statistical Methods, Volume 11(2):
  • Munni Begum (2011). On the Time-to-Event Analysis in PK/PD Modeling. Journal of
    Applied Statistical Science,
    (JASS). Vol. 18(4):569-578.
  • Munni Begum and Pranab K. Sen (2007). TK / TD Dose-Response Modeling of Toxicity.
    Environmetrics, Vol. 18, 515-525.
  • Munni Begum and Pranab K. Sen ( 2007). Location Mapping Implications for Spatial
    Prediction of Low Concentration Pollutants and the Arsenic Problem. International Journal
    of Statistical Sciences (IJSS)
    , Vol. 6, 89-100.
  • Amy C. Denham, Pamela York Frasier, Elizabeth Gerken Hooten, Leigh Belton, Warren
    Newton, Pamela Gonzalez, Munni Begum and Marci Campbell (2007). Intimate Partner
    Violence Among Latinas in Eastern North Carolina. Violence Against Women, 13, 123-140.
  • Ali, M. Masoom., Cho, J.S., Begum, M. (2006). Nonparametric Bayesian Multiple
    Comparisons for Dependence Parameter in Bivariate Exponential Populations. Journal of
    Modern Applied Statistical Methods
    , May, Vol. 5, No. 1, 92-98.
  • K.S. Kelsey, B.M. DeVellis, M. Begum, L. Belton, E.G. Hooten, M.K. Campbell (2006).
    Positive Affect, Exercise and Self- reported health in Blue- Collar women. American Journal
    of Health Behavior
    , 30(2):199-207.
  • M. Masoom Ali, Cho, J.S and Munni Begum (2005). Nonparametric Bayesian Multiple
    Comparisons for Geometric Populations. Journal of the Korean Data and Information
    Science Society
    , Vol. 16, No. 4, 1129-1140.
  • Munni Begum and Mir Masoom Ali (2004). Application of Bayesian Computational
    Techniques in Estimation of Posterior Distributional Properties for Lognormal Distribution.
    Journal of the Korean Data and Information Science Society, Vol. 15, No. 1, 227-237.