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Reproducible comparative genomics study investigating human TP53 cancer mutation hotspots across elephant TP53-related sequences, integrating sequence conservation, phylogenetic analysis, computational prioritization, and research software to explore evolutionary conservation of cancer-associated residues.
Academic research portfolio of Ritika Rajendra Rawat, focused on computational biology, evolutionary cancer genomics, comparative TP53 genomics, WGS benchmarking, and experimental analytical sciences.
Comparative evolutionary analysis of recurrent human TP53 cancer mutation hotspots across 56 mammalian species, integrating residue-level conservation, statistical testing, phylogenetic analysis, and cancer-associated mutation data to investigate evolutionary constraints on clinically relevant TP53 residues.
This repository contains an end-to-end tumour-only somatic variant-calling pipeline (GATK Mutect2 + snpEff) for triple-negative breast cancer whole-exome data, focused on BRCA1/BRCA2/TP53, built on Google Colab via Visual Studio Code.