AIエージェントの能力を拡張するClaudeスキルの完全なコレクションをご覧ください。
Transforms complex metrics into high-impact executive narratives using the Gartner-aligned What/Why/Next framework.
Applies medicinal chemistry rules and structural filters to prioritize compound libraries for drug discovery.
Performs end-to-end single-cell RNA-seq analysis workflows including quality control, clustering, and cell type annotation using the Scanpy toolkit.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Conducts rigorous, systematic evaluations of scientific manuscripts and grant proposals across various research disciplines.
Accelerates data manipulation and analysis using the high-performance Polars DataFrame library and its optimized expression-based API.
Accesses and retrieves gene expression and functional genomics data from the NCBI Gene Expression Omnibus (GEO) repository.
Builds and validates complex Bayesian models for probabilistic inference using PyMC and ArviZ.
Parses and manages Flow Cytometry Standard (FCS) files, converting biological data into NumPy arrays and dataframes for analysis.
Builds, analyzes, and visualizes complex graph structures and network data using the powerful NetworkX Python library.
Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Provides programmatic access to over 40 bioinformatics web services and databases for biological data retrieval and cross-platform analysis.
Implements type-safe SQLAlchemy repository patterns for consistent database operations and session management.
Develops and deploys specialized machine learning models for clinical healthcare data, electronic health records, and medical coding systems.
Streamlines deep learning development by organizing PyTorch code into scalable, high-performance LightningModules and automated training workflows.
Processes and analyzes mass spectrometry data using standardized metadata, peak filtering, and advanced spectral similarity metrics.
Performs differential gene expression analysis on bulk RNA-seq data using the PyDESeq2 statistical framework.
Accesses and analyzes 3D protein and nucleic acid structures from the RCSB Protein Data Bank for research and discovery.
Generates and tests scientific hypotheses automatically by combining observational data with literature insights using LLMs.
Manages large-scale N-dimensional arrays with efficient chunking, compression, and cloud-native storage integration.
Provides an advanced machine learning framework for drug discovery, molecular property prediction, and protein modeling using PyTorch.
Generates high-quality static, animated, and interactive visualizations for data analysis and scientific publication.
Manipulates, analyzes, and visualizes phylogenetic and hierarchical tree structures with biological database integration.
Generates and modifies high-quality scientific illustrations, diagrams, and concept visualizations using advanced AI models like FLUX and Gemini.
Guides users through available workflows, agents, tools, and hooks within the Claude Code environment.
Analyzes whole-slide pathology images and multiparametric imaging data using advanced machine learning and spatial graph techniques.
Access and query the COSMIC database for somatic mutations, cancer gene census, and mutational signatures to support precision oncology research.
Analyzes and optimizes Radio Access Network (RAN) coverage using cognitive consciousness and high-resolution signal strength mapping.
Accesses and queries the ChEMBL database for bioactive molecules, drug targets, and bioactivity data within medicinal chemistry workflows.
Accesses comprehensive pharmacogenomics data for precision medicine, genotype-guided dosing, and clinical decision support.
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