Ivan Ovcharenko Research Group at NCBI

	NLM Intramural Research Program

	Research Group of Ivan Ovcharenko


Research Projects	Publications	Collaborations	Resources	Group Members	Principal Investigator	Visiting us

Collaborative Projects
	Dr. Laura Elnitski NHGRI, NIH	Silencers. Identification of silencers and disease-causative silencer mutations in the human genome. Experimental validation of predicted liver silencers in Hep G2 cell lines.
	Dr. Len Pennacchio Lawrence Berkeley National Laboratory	Forebrain gene regulation. Computational analysis of sequence motifs specific to forebrain enhancers. Transgenic mouse experimentation.
	Dr. Francis Collins NHGRI, NIH	Causative mutations in Type 2 diabetes. Development of Deep Learning methods for accurate prediction of pancreatic islet enhancers and identification of disease-causative mutations in Type 2 diabetes.
	Dr. Shawn Burgess NHGRI, NIH	Regulatory networks underlying hearing regeneration. Using Deep Learning methods of enhancer prediction in zebrafish to map regulatory networks and key transcription factors partaking in hearing regeneration.
	Dr. Ben Afzali NIDDK, NIH	Experimental characterization of silencer deletions. Investigation of phenotypic effects following BACH2 silencer deletion in mice, including embryonic development and post-natal effects.
	Dr. Joseph Miano Augusta University	CRISPR/Cas9 deletion of regulatory elements in the mouse genome. Genome engineering of silencer and silencer-cluster deletions in the mouse genome.
	Dr. John Rubenstein University of California, San Francisco	Forebrain development. Reconstruction of forebrain gene regulatory networks. Identification of upstream regulators responsible for the initiation of regulatory cascades in different sub-domains of the forebrain.
	Dr. Marcelo Nobrega University of Chicago	Heart regulatory code. Coupled computational identification and experimental validation of gene regulatory elements partaking in heart development. Transgenic zebrafish experimentation.
	Dr. John Spouge NCBI, NIH	Sequence pattern analysis. Development of computational methods to identify specific sequence patterns in gene regulatory elements with shared biological functions.

Disclaimer Privacy statement