Marina Bogomolov received a B.A. in Mathematics at the Technion in 2004, M.Sc. (cum laude) in Statistics at Tel-Aviv University in 2007, and Ph.D. in Statistics at Tel-Aviv University in 2012. She was a postdoctoral fellow in the Faculty of Industrial Engineering at the Technion during 2011–2012 and a postdoctoral fellow in the Department of Statistics at Haifa University during 2012–2013. She joined the Faculty of Industrial Engineering and Management of the Technion in 2013.
M. Bogomolov and R. Heller. Discovering findings that replicate from a primary study of high dimension to a follow-up study. Journal of the American Statistical Association, 108(504): 1480–1492, 2013.
Y. Benjamini and M. Bogomolov. Selective inference on multiple families of hypotheses. Journal of the Royal Statistical Society: Series B, 76(1): 297–318, 2014.
R. Heller, M. Bogomolov, Y. Benjamini. Deciding whether follow-up studies have replicated findings in a preliminary large-scale “omics” study. Proceedings of the National Academy of Sciences of the United States of America, 111(46): 16262-16267, 2014.
C.B. Peterson, M. Bogomolov, Y. Benjamini, C. Sabatti. Many phenotypes without many false discoveries: error controlling strategies for multitrait association studies. Genetic Epidemiology, 40(1): 45–56, 2016.
C.B. Peterson, M. Bogomolov, Y. Benjamini, C. Sabatti. TreeQTL: hierarchical error control for eQTL findings. Bioinformatics, 32(16): 2556-2558, 2016.
T. Sofer, R. Heller, M. Bogomolov, C.L. Avery, M. Graff, K.E. North, A. Reiner, T.A. Thornton, K. Rice, Y. Benjamini, C.C. Laurie, K.F. Kerr. A powerful statistical framework for generalization testing in GWAS, with application to the HCHS/SOL. Genetic Epidemiology, 41(3): 251-258, 2017.
R. Dror, G. Baumer, M. Bogomolov, R. Reichart. Replicability analysis for natural language processing: testing significance with multiple datasets.Transactions of the Association for Computational Linguistics, 5(1): 471-486, 2017.
M. Bogomolov, C.B. Peterson, Y. Benjamini, C. Sabatti. Testing hypotheses on a tree: new error rates and controlling strategies. Available at https://arxiv.org/abs/1705.07529.
M. Bogomolov and O. Davidov. Order restricted univariate and multivariate inference with adjustment for covariates in partially linear models. Under review in Computational Statistics and Data Analysis.
Multiple testing, Selective inference, Replicability analysis, Order restricted inference.
Development of multiple testing procedures for selective inference.
Development of methods for replicability analysis, i.e., for discovering findings that are replicated in two or more high-dimensional studies.
Development of methods for testing hypotheses on graphs.
Applications in genomic studies.