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  • Home
  • Prabhakar Chalise, Ph.D.

Prabhakar Chalise, PhD

Assistant Professor
Department of Biostatistics & Data Science
Primary office:
(913) 945-7987


M.Sc., Statistics, Mathematics, Tribhuvan University, Kathmandu, Nepal
M.S., Statistics, University of Arkansas, Fayetteville, AR
Ph.D., Statistics, Florida State University, Tallahassee, FL

Personal Mission Statement:

My research interest is in the development and application of statistical methods in health sciences and several other areas of research. I work closely in survival analysis, longitudinal data analysis, experimental design and computational statistics. Many areas of scientific research are growing increasingly advanced in unprecedented ways due to the advent of new technologies. Such experiments generate several types and large volumes of data sets. Therefore, it is essential to develop adequate modeling approaches that will be able to utilize all available information. My research is focused in developing statistical and computational methods in analyzing such data.

Selected Publications

1.Chalise P, Koestler DC, Bimali M, Yu Q and Fridley BL. Integrative Clustering methods for High-Dimensional Molecular Data. Translational Cancer Research,3(3), 202-216, 2014  

2.Chalise P, Batzler A, Abo R, Wang L and Fridley B. Simultaneous analysis of multiple data types in Pharmacogenomic studies using weighted sparse canonical correlation analysis. OMICS: A Journal of Integrative Biology, 16(7-8):363-373, July/August 2012.

3.Fridley BL, Chalise P, Tsai Y-Y, Sun Z, Vierkant RA, Larson MC, Cunningham JM, Iversen ES, Fenstermacher D, Barnholtz-Sloan J, Asmann Y, Risch HA, Schildkraut JM, Phelan CM, Sutphen R, Sellers TA and Goode EL. Germline copy number variation and ovarian cancer survival. Frontiers in Cancer Genetics, 3:142. doi:10.3389/fgene.2012.00142, 2012.

4.Chalise P and Fridley B. Comparison of performances of various penalty functions on Sparse Canonical Correlation Analysis. Computational Statistics and Data Analysis, 56: 245-254, 2012.

5.Chalise P, Chicken E and McGee D. Baseline Age Effect on Parameter Estimates in Cox Model.  Journal of Statistical Computation and Simulation, 82(12):1767-1774, 2012.

6.Chalise P, Chicken E and McGee D. Performance and Prediction for Varying Survival Time Scales. Communications in Statistics –Simulation and Computation, 42(3): 636-649, 2013

7.Breheny P, Chalise P, Batzler A, Wang L and Fridley B. Genetic association studies of copy number variation: should assignment of copy number states precede testing? PLoS ONE 7(4): e34262. doi:10.1371/journal.pone.0034262, 2012.

8.Koestler DC, Chalise P, Cicek MS, Cunningham JM, Armasu S, Larson MC, Chien J, Block M, Kalli KL, Sellers TA, Fridley BL and Goode EL. Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer.  BMC Medical Genomics, 7(1) ,8, 2014

9.Cappendijk SLT, Carrier N., Miller GF, Chalise P, Pirvan DF, Santos AA, Hallquist M, James JR. In vivo nicotine exposure in the zebra finch; a promising innovative animal model to use in neurodegenerative disorders related research. Pharmacology, Biochemistry and Behavior, 96: 152-159, 2010.

10.Chicken, E., Chalise, P. and Loper, D. Conduit prevalence in the Woodville Karst Plain. ASCE 327: 303-312, doi: 10.1061/41003(327)29, 2008.

Additional Sites:

Department of Statistics, Florida State University


American Statistical Association


Eastern North American Region/International Biometric Society


Tribhuvan University