The research focus of the laboratory is the development of statistical and bioinformatics methods for learning fromdiverse genomics 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 bioinformatics analysis of microarray and next-gen sequencing data generated by the University of Cincinnati Genomics Core.
NIH-funded methodological research (PI: Medvedovic)
U01HL111638 Integrative statistical methods and tools for analysis of perturbation signatures
Funding Agency: NIH
The objective of this research project is the development of statistical methods and computational tools for inferring mechanistic network models by integrative analysis of diverse perturbation signatures. These methods and infrastructure will open important new avenues for interpreting results from disease-related genomics experiments by comparing them to perturbation signatures and meta-signatures. The resulting infrastructure will remove methodological and infrastructural barriers for meaningful re-use of LINCS perturbation signatures and related network models, enabling scientists throughout the world to use as resource to gain insight into the genomic conditions underlying human disease.
R01HG003749 Bayesian mixtures for modeling functional genomics data
Funding Agency: NIH
The objective of this research project is to develop a comprehensive framework for identifying statistically significant patterns in functional genomics data. Based on the Bayesian infinite mixture models, mathematical models will be developed that accommodate incorporation of prior knowledge and joint analysis of different data types in a context-specific framework. Corresponding computational tools for fitting these models will be developed, optimized and delivered to biomedical community by developing a Bioconductor package and as stand-alone command-line applications.
R21 LM009662 Integrative Probabilistic
Models for Identifying Transcriptional Modules
R03 LM 8248
Joint modeling of genomic and functional genomic data
R21HG002849-01 Computational tools for Bayesian mixture modeling of functional genomic data
Funding Institute: NHGRI
Collaborative Research Projects
Laboratory is also involved in providing bioinformatics support to several NIH-funded projects such as the Center for Environmental Genomics (CEG), Cincinnati's Breast Cancer and Environment Research Center (BCERC) and the efforts to dissect molecular mechanism of acute lung injury after exposure to hazardous chemical.