Biomedical Informatics
Jegga Lab

Jegga Research Lab

Anil Jegga, DVM, MRes, is a biological and medically-oriented computational biologist. His lab focuses on systems biology of rare disorders, drug discovery and drug response. 

The mission of the Jegga Lab is to design, develop and apply novel and robust data-driven computational approaches that will accelerate the diffusion of genomics and biomedical data into translational research and education. To this effect, they are working to convert the genomics and biomedical data deluge into systematized knowledge to help us understand the molecular basis of disease and enable therapeutic discovery.

Independently and collaboratively, they have developed and published tools that allow biologists with minimal computational experience to integrate diverse data types and synthesize hypotheses about gene and pathway function in human and mouse. These tools are designed to answer several straightforward questions that biologists frequently encounter while trying to apply systems-level analyses to specific biomedical problems. The team is currently focusing on developing and implementing systems biology-based novel computational approaches to identify drug candidates for rare lung disorders such as idiopathic pulmonary fibrosis and cystic fibrosis. They are also working to integrate and mine genomic and compound screening-based big data to identify drug repositioning and novel drug candidates and to understand the molecular basis of drug-induced diseases.

For additional information, visit Dr. Jegga’s externally hosted lab website

Major Lines of Research

Rare disease, drug repositioning, translational bioinformatics, translational genomics, systems medicine.

Software and Databases

The Jegga Lab has created several analytical servers and resources, independently and collaboratively, designed to help researchers understand biological networks and the molecular basis of disease:

Trafac – an algorithm and visualization method for compositionally similar cis-element clusters to aid in the discovery of gene regulatory regions in evolutionarily conserved noncoding genomic sequences.

GenomeTrafac – A whole genome resource for the detection of transcription factor binding site clusters associated with conventional and microRNA encoding genes conserved between mouse and human gene orthologs.

CisMols – A web-based tool for viewing computationally identified cis-regulatory modules, called CisMols, that occur in groups of coexpressed or related genes within their ortholog-pair evolutionarily conserved cis-regulatory regions.

PolyDoms – A whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease.

ToppMir – A web-based tool for ranking of microRNAs and their mRNA targets based on biological functions and context.

ToppGene Suite – a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network.

Orphan Diseasome – a web application that allows investigators to explore the orphan disease or rare disease relationships based on shared genes and shared enriched features.

PhenoHM – a human-mouse comparative phenome-genome server that facilitates cross-species identification of genes associated with orthologous phenotypes.

GATACA – a disease-centered knowledgebase that enables biomedical researchers to explore, analyze, and hypothesize genetic pathways, networks and processes responsible for disease.

ToppCluster – A multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems.

AERSMine – A multicohort-analyzing application designed to mine data across millions of patient reports from the U.S. Food and Drug Administration’s Adverse Events Reporting System (FAERS).

Contact Us

Dr. Anil Jegga at Cincinnati Children's.
Anil Goud Jegga, DVM, MRes

Mailing Address:
Division of Biomedical Informatics
3333 Burnet Ave.
Cincinnati, OH 45229-3039

Phone: 513-636-0261
Fax: 513-636-2056