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Found 77 Skills
Runs local BLAT searches for DNA sequence alignment against hg38 or CHM13 using local .2bit references. Use when a user wants to align a DNA sequence without relying on UCSC API access.
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.
Performs multiple sequence alignment of proteins with EBI Clustal Omega. Use when you need to align multiple sequences to assess similarity, domain conservation, or key residue conservation. Supports up to 4000 sequences and a maximum file size of 4 MB. Do not use to search for homologous proteins in a database (use MMseqs2, BLAST), align non-protein sequences (DNA, RNA), perform structural alignment (use Foldseek, PyMOL), or if you only have a single sequence.
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.
OpenBio API for biological data access and computational biology tools. Use when: (1) Querying biological databases (PDB, UniProt, ChEMBL, etc.), (2) Searching scientific literature (PubMed, bioRxiv, arXiv), (3) Running structure prediction (Boltz, Chai, ProteinMPNN), (4) Performing pathway/enrichment analysis, (5) Designing molecular biology experiments (primers, cloning), (6) Analyzing variants and clinical data.
Expert in Galaxy workflow development, testing, and IWC best practices. Create, validate, and optimize .ga workflows following Intergalactic Workflow Commission standards.
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.
Systematic ACMG/AMP variant classification using ToolUniverse tools. Given a genetic variant (HGVS, rsID, or gene+change), applies all 28 ACMG criteria (PVS1, PS1-4, PM1-6, PP1-5, BA1, BS1-4, BP1-7) through automated database queries and computational predictions. Produces a final 5-tier classification (Pathogenic / Likely Pathogenic / VUS / Likely Benign / Benign) with evidence summary. Use when asked to classify a variant, interpret a VUS, apply ACMG criteria, assess pathogenicity, or determine clinical significance of a germline variant.
Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.
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.
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.
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.