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Charles Blatti

Senior UIX Research Designer

-Gene Regulatory Networks

-Systems Biology

-Machine Learning in Computational Biology -Biological Data Visualization

-Precision Medicine

-FAIR Bioinformatic Workflows

I am a Research Scientist here at the National Center for Supercomputing Applications (NCSA). I received my PhD from the Department of Computer Science (CS) at the University of Illinois in 2015 and worked as a postdoc at the NIH-funded KnowEnG BD2K Center of Excellence in Big Data Computing. My research interests focus on the integration of heterogeneous prior knowledge and “-omics” data sources to model and understand biological mechanisms driving complex phenotypes including embryonic development, perturbagen responses, and social behavior. I also research regulatory characterization and modeling of co-expressed gene sets using minimal combinations of available transcriptomic, epigenomic, and computational datasets.


Blatti C*, Emad A*, Berry MJ, et al. Knowledge-guided analysis of “omics” data using the KnowEnG cloud platform. PLOS Biology. 2020.

Huang S*, Blatti C*, Sinha S, Parameswaran A. Uncovering effective explanations for interactive genomic data analysis. Patterns. 2020.

Blatti C, Sinha S. Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks. Bioinformatics. 2016.

Blatti C*, Kazemian M*, Wolfe S, Brodsky M, Sinha S. Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism. Nucleic Acids Res. 2015.

Ament SA*, Blatti CA*, Alaux C*, Wheeler MM, Toth AL, Le Conte Y, et al. New meta-analysis tools reveal common transcriptional regulatory basis for multiple determinants of behavior. Proc Natl Acad Sci U S A. 2012.

Kazemian M*, Blatti C*, Richards A, McCutchan M, Wakabayashi-Ito N, Hammonds AS, et al. Quantitative analysis of the Drosophila segmentation

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