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This skill orchestrates end-to-end bulk RNA-seq analysis, processing raw FASTQ reads through QC, trimming, alignment, and quantification to assemble a gene-level counts matrix. It then performs differential expression, pathway enrichment, and generates publication-ready figures.

Constraint-based metabolic modeling (COBRA) covers FBA, FVA, gene knockouts, flux sampling, and SBML models for systems biology and metabolic engineering analysis.

Facilitate a multi-perspective Mind Council deliberation for any question, decision, or creative challenge, providing diverse viewpoints and aiding in complex problem-solving.

Distributed computing for larger-than-RAM pandas/NumPy workflows, scaling existing code beyond memory or across clusters. Ideal for parallel file processing, distributed ML, and integration with pandas.

Search 78 public scientific, biomedical, materials science, and economic databases via REST APIs, covering fields like physics, chemistry, biology, and materials.

Molecular ML for property prediction (ADMET, toxicity) using diverse featurizers and pre-built datasets, supporting traditional ML or GNNs. It's excellent for quick experiments with pre-trained models and extensive featurization, often leveraging MoleculeNet benchmarks.

NGS analysis toolkit for BAM to bigWig conversion, QC (correlation, PCA, fingerprints), and visualization of ChIP-seq, RNA-seq, and ATAC-seq data through heatmaps/profiles (TSS, peaks).

Phylogenetic tree toolkit (ETE) for phylogenomics, offering tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy integration, and visualization (PDF/SVG).

Performs comprehensive exploratory data analysis on scientific data files across 200+ formats. It automatically detects file types and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations to understand data structure, content, and quality.

Parses FCS (Flow Cytometry Standard) files v2.0-3.1. Extracts events as NumPy arrays, reads metadata/channels, and converts to CSV/DataFrame for flow cytometry data preprocessing.

A Python framework for computational fluid dynamics simulations, supporting Navier-Stokes (2D/3D), shallow water, and stratified flows, as well as turbulence and vortex dynamics analysis. It offers pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation, including photos, illustrations, artwork, and concept art, but not technical diagrams. For technical diagrams, use the scientific-schematics skill.