Skill UI

Retrieve AlphaFold’s AI-predicted protein models via UniProt IDs, download CIF/PDB coordinates, inspect confidence metrics, and feed them into structural analysis or drug-discovery pipelines.

Direct REST API access to UniProt for searching proteins, fetching FASTA sequences, mapping identifiers, selecting annotations, and streaming large datasets within Python workflows.

Provides direct REST API access to UniProt, the premier resource for protein sequence and functional information. This skill enables users to search proteins by name, gene, or accession number, retrieve sequences in FASTA format, perform cross-database ID mapping (e.g., Ensembl, RefSeq), and analyze functional annotations (GO terms) for building comprehensive bioinformatics pipelines.

Python client for bioinformatics services such as UniProt, KEGG, ChEMBL, Reactome, QuickGO and UniChem, enabling cross-database protein annotation, pathway retrieval, compound cross-referencing and integrated biological data workflows.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

Query the UniProt REST API for protein sequences and annotations. Search by gene, accession or organism, fetch FASTA files, map IDs across Ensembl, RefSeq and PDB, customize returned fields, and stream large datasets programmatically.

Access AlphaFold's 200M+ AI-predicted protein structures via UniProt IDs and APIs, download PDB/mmCIF files, and analyze pLDDT/PAE confidence metrics for structural biology and drug discovery.