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

mRNA Open Release Study

Local-first multi-agent AI for precision oncology (TP53): AlphaFold/ESMFold structures, ESM-2 variant scoring, ΔΔG stability, AutoDock Vina molecular docking and a per-agent reasoning audit benchmarked against ClinVar/IARC. Offline on 8 GB RAM; HL7 FHIR R4; 566 tests. Research use only.

Bioinformatics portfolio: TP53 from variant to patient — structural bioinformatics, transcriptomics and survival analysis.

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

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

Live TP53 bioinformatics pipeline: NCBI Entrez retrieval, DNA translation & 6-frame ORF discovery, pairwise alignment, multi-species phylogenetics, InterPro domain annotation, and a cancer-mutation biochemistry heatmap. BioPython + Streamlit; 63 tests, CI/CD.

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

Computational analysis of ~10,000 TP53 mutations: fitness landscape, mutation classes, codon adaptation and epistasis (B.Tech thesis, research at IIT Bombay)

nci-webtools-dceg-tp53

Evolutionary and comparative analysis of vertebrate TP53 proteins using multiple sequence alignment, conservation analysis, and phylogenetic reconstruction.

Mapping the TP53 variant landscape: where clinically significant missense variants cluster across p53 protein domains (ClinVar + UniProt).

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