Pinned Repositories
Genomic-Data-Exploration-Visualizing-Genetic-Variants-and-Allelic-Imbalance
Advanced bioinformatics analysis of RNA sequencing data and genomic databases using R. Explore allelic imbalances, SNP variants, and phylogenetic trees to uncover genetic insights and visualize complex data interactions.
gitikabhardwaj
Config files for my GitHub profile.
Precision-Medicine-Genomic-Insights-and-Personalized-Healthcare
This repository is dedicated to advancing precision medicine through Python-based bioinformatics analyses. It emphasizes genomic data processing, analysis of genetic variability, and the development of predictive models that tailor healthcare to individual genetic profiles.
Statistical-Analysis-of-A2-noradrenergic-neuron-activation-in-fear-conditioned-rats
This repository explores the activation patterns of A2 noradrenergic neurons in fear-conditioned rats, using statistical analyses like t-tests and linear regression in R. It focuses on the differences in dopamine β-hydroxylase (DbH) neuron activation between various environmental conditions.
gitikabhardwaj's Repositories
gitikabhardwaj/Genomic-Data-Exploration-Visualizing-Genetic-Variants-and-Allelic-Imbalance
Advanced bioinformatics analysis of RNA sequencing data and genomic databases using R. Explore allelic imbalances, SNP variants, and phylogenetic trees to uncover genetic insights and visualize complex data interactions.
gitikabhardwaj/gitikabhardwaj
Config files for my GitHub profile.
gitikabhardwaj/Precision-Medicine-Genomic-Insights-and-Personalized-Healthcare
This repository is dedicated to advancing precision medicine through Python-based bioinformatics analyses. It emphasizes genomic data processing, analysis of genetic variability, and the development of predictive models that tailor healthcare to individual genetic profiles.
gitikabhardwaj/Statistical-Analysis-of-A2-noradrenergic-neuron-activation-in-fear-conditioned-rats
This repository explores the activation patterns of A2 noradrenergic neurons in fear-conditioned rats, using statistical analyses like t-tests and linear regression in R. It focuses on the differences in dopamine β-hydroxylase (DbH) neuron activation between various environmental conditions.