Guides Claude to perform fast genomic interval operations and bioinformatics file I/O (BED/VCF/BAM/GFF) on Polars DataFrames with polars-bio.
A skill that guides classical machine learning in Python with scikit-learn — classification, regression, clustering, preprocessing, evaluation and tuning — following leakage-free best practices.
A skill that guides Claude in building, analyzing, and visualizing networks and graphs with Python's NetworkX.
Run end-to-end proteomics and metabolomics LC-MS/MS analysis with ready-made pyOpenMS CLI scripts.
A skill that guides Claude through choosing SHAP explainers and maskers, computing, validating, and visualizing feature attributions on SHAP 0.52.
A fail-closed EDA skill that profiles authorized local scientific files, audits missingness, leakage and outliers, and drafts a rigorous report without exposing raw values.
A skill that steers Claude toward idiomatic Matplotlib code for publication-quality figures.
Build, test, and analyze bounded process-based discrete-event simulations in SimPy with correct event semantics and replication-based output analysis.
Guides you through UMAP embeddings, parameter tuning, and clustering preprocessing with ready-to-run scikit-learn code.
Guides Claude through deepTools workflows for converting, QC-ing and visualizing ChIP-seq, RNA-seq and ATAC-seq data.
Correct, idiomatic pysam workflows for reading, querying, filtering, and writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, and tabix data.
Discovers and applies curated Hugging Face datasets, models, and Spaces across 17 scientific domains, from protein design to climate modeling.
Plans studies by computing required sample size, minimum detectable effect, and power curves via closed-form formulas or Monte Carlo simulation.
Runs ORA and (pre)ranked GSEA on gene lists or ranked gene tables across GO, KEGG, Reactome and MSigDB, then interprets and visualizes the results.
Turns a plain-English request like "find dentists in Berlin" into a validated, locally-run Docker crawl of Google Maps for business leads, contacts, and reviews.
A canonical contract for AI research that runs without you: bounded question budget, search-plan gate, Fact/Inference/Assumption labels, do-not-invent lists, and a stable diffable output schema.
Guides Claude to infer transcription factor–target gene networks from expression data using arboreto's GRNBoost2 and GENIE3.
Teaches Claude the correct, up-to-date patterns for creating, reading, writing, concatenating and subsetting AnnData (.h5ad/zarr) objects in single-cell workflows.
Look up precomputed AlphaGenome Atlas AVI scores and call the AlphaGenome model on demand to rank and mechanistically interpret non-coding regulatory SNVs.
Searches scientific literature through the BGPT MCP server and returns 25+ structured fields extracted from full-text papers.