Today is Monday, Apr. 23, 2018

Department of Environmental Health

Center for Environmental Genetics

Bioinformatics Core

The CEG Bioinformatics core assists investigators in converting their genomic and protein data into meaningful information through the use of appropriate data-management and computational/statistical tools. The core is led by Dr. Mario Medvedovic, Professor of Environmental Health and a member of the UC Cancer Institute.  Dr. Medvedovic also leads the UC component of a multi-institutional team that was  awarded a 5-year, $19.7 million grant (2015-2020) from the National Institutes of Health (NIH) to create a data coordination center for an NIH program seeking insight into how cells react to drugs and toxins. The grant is part of the NIH’s Big Data to Knowledge (BD2K) initiative, which brings together UC, the Icahn School of Medicine at Mount Sinai in New York and the University of Miami (FL) in the mission and work of the BD2K-LINCS Perturbation Data Coordination and Integration Center.

 

Mario Medvedovic, MSc, PhD
Email: medvedm@ucmail.uc.edu
Statistical issues in designing functional genomic and proteomic experiments; statistical analysis, data mining, Bayesian machine learning. Laboratory for Statistical Genomics and Systems Biology.

Jarek Meller, PhD
Core Co-Leader
Protein structure modeling, structure based functional assessment. Bioinformatics Portal

Alexey Porollo, PhD
Research Assistant Professor, Center for Autoimmune Genomics and Etiology (CAGE)
with joint appointment at the Division of Biomedical Informatics
Computational biology, portal development, web applications; eLab Portal

Bruce Aronow, PhD
Bioinformatics and Functional Genomics
Bioinformatics, transcriptional regulation during development

Ge Zhang, PhD
Statistical Genetics
Analysis of microarray-based SNP genotyping data

Kaustubh Shinde
Database Administrator. MySQL database management, MAGE-OM standard, Web programming.

Michael Wagner, PhD
Research Associate Professor UC/CCHMC Pediatrics/Medical Bioinformatics
Proteomic Informatics Management and analysis of proteomics data.