Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database...

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微信公众号文章发布完整流程管理，包括AI辅助创作、图片生成、排版和发布。

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

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UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

Lance des dés pour jeux de rôle (Basic Fantasy RPG). Supporte d4, d6, d8, d10, d12, d20, d100. Notation standard comme 2d6+3, 4d6kh3 (keep highest). Avantage et désavantage. Utilisez pour tout jet...

Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health...

Run accessibility and visual design review on components. Use when reviewing UI code for WCAG compliance and design issues.

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

Complete guide for Pyth Network - decentralized oracle providing real-time price feeds for DeFi. Covers price feed integration, confidence intervals, EMA prices, on-chain CPI, off-chain fetching,...

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Complete Raydium Protocol SDK - the single source of truth for integrating Raydium on Solana. Covers SDK, Trade API, CLMM, CPMM, AMM pools, LaunchLab token launches, farming, CPI integration, and...

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin...

Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model...