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NIT Rourkela

Advancing Animal Bioinformatics: Insights into Omics Data for Improved Livestock Health and Production at NIT Rourkela

The Bioinformatics Center at NIT Rourkela has a specific mandate to provide bioinformatics infrastructure and training in Bioinformatics and Computational Biology, with a focus on Animal Bioinformatics. Furthermore, ongoing research delves into the analysis of omics data related to production diseases such as mastitis, ketosis, and milk fever, along with investigations into male infertility. The center is committed to establishing robust infrastructure and computer support for bioinformatics and computational biology research at NIT Rourkela and neighboring institutions. It actively engages in the development of bioinformatics tools and techniques, organizes training workshops and seminars, and conducts research focusing on big data analysis of transcriptome and microbiome for animal biotechnology. This includes modeling biomolecular systems associated with nuclear reprogramming and stem cell pluripotency, as well as identifying novel inhibitors for therapeutic targets in diseases like mastitis affecting animal production.

Mukesh Gupta

Among its accomplishments, the center has successfully identified the RNA population landscape in goat spermatozoa and developed an innovative pipeline for predicting circRNA  from RNA-seq datasets. It has reported on the mechanism of capacitation by heparin and L-arginine in goat spermatozoa.

Additionally, the center has predicted potential molecular markers of bovine mastitis through meta-analysis. Notably, the center plays a pivotal role in training over 50 personnel annually in bioinformatics and computational biology. Their research contributions are published in SCI- indexed journals, and the software developed is copyrighted. They have designed a user friendly GUI software providing access to various biological databases and bioinformatic tools, freely available to academia. A one-stop graphical user interface (GUI) has been created for analyzing genomic, transcriptomic, and proteomic data, coupled with fast rebooting capabilities for workstation maintenance. Another software simulating the behavior of stem cells and their progenies within and outside the stem cell niche has been developed. Emphasizing animal bioinformatics, particularly in the analysis of high-throughput omics data on mammary glands and reproductive tissue, the BIC maintains strong connections with wet labs for experimental validation.

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