Query genomic and proteomic resources via CLI or Python APIs.
npx skills add https://github.com/shushuzn/Rairos --skill gget-shushuzn
Please help me install this Agent Skill. Skill: gget Source: https://github.com/shushuzn/Rairos/tree/main/skills/gget Command: npx skills add https://github.com/shushuzn/Rairos --skill gget-shushuzn
gget eliminates slow, fragmented research lookups by providing a single, consistent interface to query multiple genomics, proteomics, structure, expression, and enrichment resources without switching tools or manually reformatting results.
Ask the AI to run: "Search for GABA-related genes in human with gget search -s human gaba gamma-aminobutyric and return the top results as JSON."
High-intent search queries and answers about installing and using this skill.
Querying multiple bioinformatics databases for gene sequences and annotations is done through a unified interface that retrieves gene references, identifiers, sequences, and biological annotations across genomic and proteomic resources without switching tools.
Yes, you can retrieve protein structures and run sequence alignment from a single CLI tool. The interface supports integrated BLAST/BLAT searches, multiple sequence alignment, local protein alignment via DIAMOND, and structure retrieval or prediction using PDB and AlphaFold.
Running enrichment analysis and disease association queries on a gene list is best handled by an end-to-end research workflow that fetches sequences, executes enrichments, and pulls candidate disease and drug association links in one repeatable pipeline.
Gene search and expression correlation requires module-scoped dependency setup for specific resources. You must configure dependencies for AlphaFold, ELM, and cellxgene to enable structure prediction, motif prediction, and expression correlation respectively.
Serializing bioinformatics query results into JSON, CSV, FASTA, or PDB formats is handled natively by the deterministic CLI and Python interface. The interface provides output serialization options alongside species and assembly selection parameters.
Using a unified local query tool instead of manually switching between genomic and proteomic resources eliminates slow, fragmented research lookups by preventing manual result reformatting and providing a single consistent API across multiple databases.
silversteinRetrieve genomic, sequence, structural, and functional evidence for genes and proteins via unified gget modules.
zongtingweiFetch protein sequences, annotations, and PDB cross-references from UniProt via REST API.
Zeyuyang-0420Automate molecular biology tasks with Biopython for sequence and alignment analysis.
jackspaceAccess 40+ bioinformatics services and databases via a unified Python API.
