Characterization of Germline variants
An Open Source Web Application for Genetic Data (SNPs) Data Crawling
Variant Agents: Multi-Agent Genomic Analysis
Whole genome sequencing analysis pipeline for consumer hardware. 100% local, Docker-powered, free and open source.
PyGeneBe: A Python client seamlessly integrating with the GeneBe platform, offering efficient annotation of genetic variants through its API, while supporting pandas, VCF file formats, and HGVS parsing
ClinVar Submission API Made Easy
Short Linear Motif (SLiM) Analysis in the context of human diseases
A bioinformatics pipeline to identify the best available PDB structures for all available variants for specified genes of interest
🧬 Open-source genotype analysis toolkit. The open-source Promethease replacement.
An AI-driven genomic intelligence system delivering structured ClinVar interpretation and high-precision exon, intron, and gene queries using the Model Context Protocol (MCP).
R script to 1) Extract missense variants that had been observed in "clinical testing" (as opposed to "literature only") in ClinVar. 2) Calculating movability and reappearance parameters using the aggregated and capped Invitae variant counts. 3) Apply the movability and reappearance parameters to ClinVar genes, calculating their movability- and r…
Identification of cancer-causing variants
Privacy-first genetic exploration dashboard. Analyze raw DNA from 23andMe, AncestryDNA, MyHeritage, and Genera against ClinVar + PharmGKB — entirely on your machine. Optional local AI interpretation via Ollama and PT-BR neural translation via Argos.
AlphaFold MCP server composing 8 biomedical sources into a local knowledge graph
Machine Learning-based Prediction of Pathogenicity for Protein Variants in ClinVar Database
Data repository for NeurIPS 2022 LMRL workshop paper.
"NIHDataFetcher" is a GitHub repository with scripts for accessing and fetching data from various NIH databases like GEO and PubMed. It provides code examples to retrieve GEO datasets, search PubMed, and load ClinVar data. Ideal for researchers and data scientists working with biomedical information.
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