Claude-Science-for-win

Cheminformatics (mirrors Claude Science's cheminformatics skill). RDKit for descriptors/fingerprints/similarity and molecule drawing, ChEMBL for bioactivity, SAR/screening. Use for small molecules, SMILES, molecular descriptors, ChEMBL, medicinal chemistry. Needs the sci-bio env (rdkit).

CRISPR screen design & analysis (mirrors Claude Science's CRISPR screen skill). Designs guide libraries, runs enrichment/depletion analysis on read counts, and traces every hit back to its sgRNA support. Use for sgRNA libraries, screen counts, enrichment analysis.

Reproducible data analysis. Uses pandas/numpy/scipy/statsmodels for cleaning, statistics, and modeling; scripts and random seeds all land in the run, and every reported number is recomputable. Use to analyze tabular/matrix data, run statistical tests, or model.

Publication-grade figures. Uses matplotlib to generate figures from a script (never hand-drawn, never pasted from an unknown source); each figure has a rerunnable script. Layer the global CCF-Figure skill for figure conventions / top-venue layout. Use to draw paper figures and iterate to publication quality.

Provenance-backed literature review. Searches PubMed / Europe PMC / arXiv (connectors/literature.py), dedupes, synthesizes by theme, and attaches a DOI/PMID to every conclusion. Use when you need a literature review, evidence for a claim, or a related-work section.

Manuscript writing and iteration to publication quality. Organizes IMRaD structure, inserts run-generated figures/tables, manages references, and produces docx/pdf/md. Layer the global docx / doc-coauthoring / pdf skills. Use to write a paper draft, methods, results, and iterate.

Phylogenetics & evolution (mirrors Claude Science's phylogenetics skill). MAFFT alignment + IQ-TREE tree building + selection/ancestral reconstruction, results shown next to the sequences that produced them. Use for multiple-sequence alignment, phylogenetic trees, selection analysis.

Protein structure & protein language models (mirrors Claude Science's protein structure/language-model skill). PDB/UniProt pull & compare structures, Biopython parsing, ESM sequence representation; structure prediction (OpenFold3/Boltz-2/Evo2) via BioNeMo placeholder (needs GPU/NVIDIA). Use for protein structure, PDB, structure comparison, protein language models.

Single-cell RNA-seq analysis (mirrors Claude Science's single-cell skill). scanpy/anndata pipeline QC->normalize->HVG->PCA->neighbors->Leiden->UMAP->markers->annotation, publication figures. Use for scRNA-seq, count matrices, cell clustering/annotation. Needs the sci-bio env.