Renesh Bedre, Ph.D.
Bioinformatics data scientist
Appointments and Education
Dr. Renesh Bedre is a Bioinformatics data scientist having 8 years of experience in
Bioinformatics, statistics, and genetics. He has expertise in high-throughput
transcriptome and whole genome sequencing data analysis.
He received Ph.D. from Louisiana State University at Baton Rouge, USA in 2016. Currently, He is working as a postdoctoral research associate and Bioinformatics data scientists at Texas A&M University.
He has extensive experiences in large-scale gene expression profiling, sequence assemblies, molecular biomarker discovery, functional annotation, GWAS, development of algorithms and software pipelines, and data visualization. He has worked on the genetics of simple (Rice, Arabidopsis, Brachypodium, Tomato) to complex (Sugarcane, Spartina, Cotton, Potato) plants.
He also has extensive experiences in the development of standalone software programs, automated software pipelines, web servers, and databases for analysis of large-scale datasets generated from next-generation sequencing (NGS) platforms. He has strong proficiency in Python, R/Bioconductor, Perl, PostgreSQL, Bash, Django, open-source bioinformatics tools, high-performace computing (HPC), CyVerse, and GitHub.
- Gene expression and biomarker discovery
- Plant biology
- Standalone software programs, web servers, and databases development
- Development of new computational methodologies for NGS analysis
- High Performance Computing for big data analysis
- Parallel computing (shared and distributed), Machine learning
- Python, R/Bioconductor, Perl, PostgreSQL, Linux, HPC, CyVerse, Docker
Postdoctoral Research Associate, 2016-Present
Texas A&M AgriLife Research, TX, USA
Ph.D. in Bioinformatics and plant biology, 2011-2016
Louisiana State University, baton Rouge, LA, USA
M.S. in Bioinformatics, 2009-2011
Indian Institute of Information Technology, Allahabad, UP, India
Computational biology, Bioinformatics, Genomics, Transcriptomics, Gene expression, GBS, GWAS, high-throughput data analysis and interpretation, Statistics, phylogenetics, genotyping, biomarkers, Functional annotation, Population genomics, Gene co-expression network, RNA-seq, RAD-seq, AgSeq, Genetics, Software and database development, data integration, Cloud-based computing, GitHubPlease, read CV for research experience, awards, and achievements