Query 20+ bioinformatics databases via CLI or Python API.
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill gget-k-dense-ai
Please help me install this Agent Skill. Skill: gget Source: https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/gget Command: npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill gget-k-dense-ai
gget provides a unified, fast interface to 20+ bioinformatics databases, enabling researchers to perform gene discovery, sequence retrieval, enrichment, and analysis without juggling multiple tools.
Run gget search BRCA1 --species homo_sapiens to see basic gene results.
High-intent search queries and answers about installing and using this skill.
You can retrieve gene sequences and information from multiple bioinformatics databases at once using a unified CLI or Python API that queries Ensembl, UniProt, NCBI, and others simultaneously. This provides fast lookups for interactive research or batch workflows without juggling separate tools.
The best way to query Ensembl and UniProt for gene expression and disease associations in Python is using a modular API that directly interfaces with these databases. You can run targeted commands to fetch expression data from ARCHS4 or disease associations from OpenTargets within scripted pipelines.
Yes, you can perform batch sequence retrieval and enrichment analysis across 20+ databases. The tool supports scripted pipelines for reproducible analyses, allowing you to process large batches of gene queries for sequences, expression data, and enrichment results in a single workflow.
Yes, this bioinformatics tool supports AlphaFold structure lookups and COSMIC mutation data. It provides direct access to both resources alongside cBioPortal and OpenTargets, enabling you to retrieve structural predictions and disease or drug associations for specific genes.
To search for a specific gene like BRCA1 across different species, you use the search function with the gene name and species parameter, such as specifying homo_sapiens. This queries Ensembl to return matching gene results and relevant sequence data quickly.
Limitations of using a unified query tool for bioinformatics database access include reliance on the uptime and data structure of external resources like Ensembl and NCBI. While it provides clear error handling, complex or highly specialized queries outside its 20+ supported databases may still require direct database access.
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