Laboratory for Statistical Genomics and Systems Biology

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Mario Medvedovic, PhD.

Associate Professor

email: Mario.Medvedovic@uc.edu

Phone: 513-558-8564

Fax: 513-558-8564

Division of Epidemiology and Biostatistics

Department of Environmental Health

University of Cincinnati Medical Center

 3223 Eden Av. ML 56

Cincinnati OH, 45267-0056 

 

 

The research focus of the laboratory is the development of Bayesian hierarchical models for unsupervised and semi-supervised learning from diverse data types, and the application of such methods through interdisciplinary biomedical efforts. Members of the laboratory are also developing protocols for comprehensive data management and the statistical analysis of microarray data that is generated by the University of Cincinnati Genomics Core.

The laboratory is spanning two different departments within the University of Cincinnati College of Medicine and the Cincinnati Children's Hospital Medical Center.

 

Selected Methodological Manuscripts (see all publications)

  • Freudenberg JM, Joshi VK, Medvedovic M: CLEAN: CLustering Enrichment ANalysis. BMC Bioinformtics 10:234. 2009. (Software).

  • Sartor MA, Leikauf GD, Medvedovic M: LRpath: A logistic regression approach for identifying enriched biological groups in gene expression data. Bioinformatics, 15;25(2): 211-7. 2009. (Support Page) (preprint)

  • Liu X, Jessen W, Sivaganesan S, Aronow BJ, Medvedovic M: Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data. BMC Bioinformatics, 8(1):283. 2007.

  • Sartor MA, Tomlinson CR, Wesselkamper SC, Sivaganesan S, Leikauf GD, and Medvedovic M, Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments. BMC Bioinformatics 7: 538, 2006. (Support Page)

  • Liu, X., Sivaganesan, S., Yeung, K.Y., Guo, J., Bumgarner, R.E., Medvedovic M. Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray datasets. Bioinformatics 22:1737-44. 2006. (Support Page)(preprint).

  • Medvedovic, M., Wiest, J.S. DNA Microarrays and Computational Analysis of DNA Microarray Data in Cancer Research. In Molecular Carcinogenesis, Warshawsky and Landolph, CRC Press .  (preprint)

  • Medvedovic M., Guo, J., Bayesian Model-Averaging in Unsupervised Learning From Microarray Data. BIOKDD 2004. (PDF)

  • Medvedovic, M., Yeung, K.Y., Bumgarner, R.E. Bayesian Mixtures for Clustering Replicated Microarray Data. Bioinformatics. 20: 1222-1232, 2004.(PDF)

  • Medvedovic M., Sivaganesan S. Bayesian infinite mixture model based clustering of gene expression profiles. Bioinformatics 18: 1194-1206, 2002. (PDF)

  • Medvedovic M., Succop P., Dixon K., Shukla R. Clustering mutational spectra via classification likelihood and Markov Chain Monte Carlo Algorithm. Journal of Agricultural, Biological and Environmental Statistics, 6: 19-37. 2001.(PDF)

  • Medvedovic M. Identifying statistically significant patterns of expression via Bayesian Infinite Mixture Models. Critical Assessment of Microarray Data Analysis (CAMDA) 2000. (PDF)

  • Medvedovic M. Clustering Multinomial Observations via Classification Likelihood and MCMC Algorithms. Proceedings of the Joint Statistical Meeting 2000: Statistical Computing Section. , 48-51. 2000. (PDF)

  • Medvedovic M. (2000) Determining the number of replicates needed to detect differentially expressed genes in DNA array experiments (not-published manuscript)

Selected Biomedical Publications

  • Medvedovic M, Gear R, Freudenberg JM, Schneider J, Bornschein R, Yan M, Mistry MJ, Hendrix H, Karyala S, Halbleib D, Heffelfinger S, Clegg DJ, Anderson MW. Influence of Fatty Acid Diets on Gene Expression in Rat Mammary Epithelial Cells.  Physiol Genomics 2009 Apr 7. (Support Page)

  • Medvedovic M, Tomlinson CR, Call MK, Grogg M, Tsonis PA. Gene expression and discovery during lens regeneration in mouse: regulation of epithelial to mesenchymal transition and lens differentiation.  Mol Vis. 8;12:422-40. 2006.

  • Stringer JR, Larson JS, Fischer JM, Medvedovic M, Hersh MN, Boivin GP, Stringer SL. Modeling variation in tumors in vivo.  Proc Natl Acad Sci U S A. 2005 Feb 3; [Epub ahead of print].

  • Puga, A., Sartor, M.A., Huang, M-Y, Kerzee, K.J., Wei, Y-D, Tomlinson, C.R., Baxter, C.S., Medvedovic, M. Gene expression profiles of mouse aorta and cultured vascular smooth muscle cells are widely different, yet show common responses to dioxin exposure. Cardiovascular Toxicology 4(4):385-404.2004.  (Abstract)

  • Sartor, M.A., Schwanekamp, J., Halbleib, D., Mohamed, I., Karyala, S., Medvedovic, M. and Tomlinson, C.R. Microarray results improve significantly as hybridization approaches equilibrium. Biotechniques 36: 790-796, 2004.(Abstract)

  • Nikiforova M., Stringer J.R., Blough R., Medvedovic M., Fagin J.A., Nikiforov Y.A. Proximity of Chromosomal Loci That Participate in Radiation-Induced Translocations in Human Cells. Science, 290: 138-141. 2000.(Abstract) (Full Text - requires Science online subscription)

  • Puga A., Maier A., Medvedovic M. The transcriptional signature of dioxin in human hepatoma HepG2 cells. Biochemical Pharmacology. 60: 1129-1142. 2000. (Abstract)

 

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