tp53

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.

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.

Academic research portfolio of Ritika Rajendra Rawat, focused on computational biology, evolutionary cancer genomics, comparative TP53 genomics, WGS benchmarking, and experimental analytical sciences.

Tools for programmatically annotating VCFs with the Seshat TP53 database

A precision oncology dashboard for ranking and prioritizing TP53 cancer mutations by druggability. Integrates structural biology, quantum chemistry (IBM), and clinical trial data to identify the most promising targets for small-molecule therapy development.

Find tumor gene mutation rates (TP53 and STAT5A) using cancer datasets from The Cancer Genome Atlas.

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.

Proyecto final de la clase de Bioinformática

nci-webtools-dceg-tp53

A Hybrid Quantum-Classical AI Pipeline for TP53 Mutation Pathogenicity Prediction

Bioinformatics pipeline for TP53 tumor suppressor gene — DNA to mRNA, BLAST, AlphaFold2 structure prediction, and GNINA ligand docking.