The research areas I pursue include translational bioinformatics - computational drug discovery and drug repositioning, network medicine, systems biology of disease and drug response.
My team and I are attempting to solve biomedical problems by designing, developing and implementing innovative and novel computational methods. These approaches will speed up the diffusion of genomics within biomedical research and education and transform the genomics data overflow into structured knowledge to aid translational research.
Some of the most trailblazing discoveries made within my lab include bioinformatics applications (ToppGene Suite) and rare disease network analysis. We have also discovered drug repositioning candidates for rare diseases such as cystic fibrosis and idiopathic pulmonary fibrosis.
I continuously believe that no problem is unsolvable. Problems and challenges are essential prompts for tapping into human creativity. Over the years, I’ve mentored more than 24 PhD and master’s students and served as a chair, co-chair or committee member.
During my early years of research, I realized that the stimulus for technological advancement to further evolve into translational discoveries is through team science and collaborative research.
I have received multiple awards and recognitions throughout my career including:
I have more than 20 years of experience in biomedical informatics and began working at Cincinnati Children’s in 2001. My research has been published in well-respected journals, such as Nature Biotechnology, Proceedings of the National Academy of Sciences of the United States of America, The American Journal of Human Genetics, Nucleic Acids Research, Briefings in Bioinformatics and Nature Neuroscience.
Master of Research: University of York, England, UK.
Master of Veterinary Science: College of Veterinary Science, Hyderabad, India.
Bachelor of Veterinary Science & Animal Husbandry: College of Veterinary Science, Hyderabad, India.
Biomedical Informatics
Consensus Gene Co-Expression Network Analysis Identifies Novel Genes Associated with Severity of Fibrotic Lung Disease. International Journal of Molecular Sciences. 2022; 23.
Secondary analysis of transcriptomes of SARS-CoV-2 infection models to characterize COVID-19. Patterns. 2021; 2:100247.
Secondary analysis of transcriptomes of SARS-CoV-2 infection models to characterize COVID-19. Patterns. 2021; 2:100247.
Secondary analysis of transcriptomes of SARS-CoV-2 infection models to characterize COVID-19. Patterns. 2021; 2:100247.
Secondary analysis of transcriptomes of SARS-CoV-2 infection models to characterize COVID-19. Patterns. 2021; 2:100247.
Inhibition of Aurora Kinase B attenuates fibroblast activation and pulmonary fibrosis. EMBO Molecular Medicine. 2020; 12:e12131.
Changing Trends in Computational Drug Repositioning. Pharmaceuticals. 2018; 11.
Unsupervised gene expression analyses identify IPF-severity correlated signatures, associated genes and biomarkers. BMC Pulmonary Medicine. 2017; 17:133.
Hsp90 regulation of fibroblast activation in pulmonary fibrosis. JCI insight. 2017; 2:e91454.
Data mining differential clinical outcomes associated with drug regimens using adverse event reporting data. Nature Biotechnology. 2016; 34:697-700.
Anil Goud Jegga, DVM, MRes, Mayur Sarangdhar, PhD ...3/15/2023
Anil Goud Jegga, DVM, MRes4/6/2021
Anil Goud Jegga, DVM, MRes8/6/2020
Anil Goud Jegga, DVM, MRes, Mayur Sarangdhar, PhD ...6/29/2019