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Found 77 Skills
Use when writing Python that processes biological sequences (DNA/RNA/protein) with the seqpro package — encoding, one-hot, k-mer shuffling, reverse complement, GC content, variable-length sequence batches, or anything involving seqpro's `Ragged` array. Covers the seqpro API surface and the conventions you need to use it correctly.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
Analyze microbiome and metagenomics data using MGnify, GTDB, ENA, and literature tools. Search studies by biome/keyword, retrieve taxonomic profiles and functional annotations, classify genomes with GTDB taxonomy, and find related publications. Use for human gut microbiome, soil/ocean metagenomics, and environmental microbiology research.
Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
Structure similarity search with Foldseek. Use this skill when: (1) Finding similar structures in PDB/AFDB databases, (2) Structural homology search, (3) Database queries by 3D structure, (4) Finding remote homologs not detected by sequence, (5) Clustering structures by similarity. For sequence similarity, use uniprot BLAST. For structure prediction, use chai or boltz.
ESM2 protein language model for embeddings and sequence scoring. Use this skill when: (1) Computing pseudo-log-likelihood (PLL) scores, (2) Getting protein embeddings for clustering, (3) Filtering designs by sequence plausibility, (4) Zero-shot variant effect prediction, (5) Analyzing sequence-function relationships. For structure prediction, use chai or boltz. For QC thresholds, use protein-qc.
Provide actionable treatment recommendations for cancer patients based on molecular profile. Interprets tumor mutations, identifies FDA-approved therapies, finds resistance mechanisms, matches clinical trials. Use when oncologist asks about treatment options for specific mutations (EGFR, KRAS, BRAF, etc.), therapy resistance, or clinical trial eligibility.
Rapid pathogen characterization and drug repurposing analysis for infectious disease outbreaks. Identifies pathogen taxonomy, essential proteins, predicts structures, and screens existing drugs via docking. Use when facing novel pathogens, emerging infections, or needing rapid therapeutic options during outbreaks.
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.
Integrate structural biology data with proteomics for drug target validation. Retrieves protein structures from PDB (RCSB, PDBe), AlphaFold predictions, antibody structures (SAbDab), GPCR data (GPCRdb), binding pocket analysis (ProteinsPlus), and ligand interactions (BindingDB). Use when asked to find structures for a drug target, identify binding site ligands, cross-validate drug binding with structural data, assess structural druggability, or compare experimental vs predicted structures.
Immunology research workflows using ToolUniverse tools. Covers antibody-antigen structural analysis (SAbDab, TheraSAbDab), immune protein interactions (IntAct, BioGRID), epitope and T-cell/B-cell assay data (IEDB), immunoglobulin gene databases (IMGT), cytokine/receptor signaling (OpenTargets, GWAS), clinical safety data for immune diseases (FAERS, clinical trials), autoimmune disease genetics (Orphanet), and immune pathway analysis (KEGG, Reactome). Use when researchers ask about antibody targets, immune signaling networks, autoimmune genetics, immunotherapy safety, epitope discovery, or immune pathway enrichment.
Ligand-aware protein sequence design using LigandMPNN. Use this skill when: (1) Designing sequences around small molecules, (2) Enzyme active site design, (3) Ligand binding pocket optimization, (4) Metal coordination site design, (5) Cofactor binding proteins. For standard protein design, use proteinmpnn. For solubility optimization, use solublempnn.