data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Analyzes complex mass spectrometry data for proteomics and metabolomics using Python bindings for the OpenMS library.
Facilitates computational molecular biology tasks using the Biopython library for sequence analysis, structural bioinformatics, and NCBI database integration.
Accesses over 40 major bioinformatics web services and databases through a unified Python interface for seamless biological data retrieval and analysis.
Automates the generation, refinement, and testing of scientific hypotheses by integrating observational data with existing literature.
Simplifies scientific research by providing standardized access to over 600 tools for bioinformatics, drug discovery, and computational biology.
Queries the openFDA API to retrieve comprehensive data on drugs, medical devices, food safety, and adverse events.
Queries the openFDA API to analyze regulatory data for drugs, medical devices, food safety, and chemical substances.
Queries the openFDA API to retrieve comprehensive data on drug safety, medical device clearances, food recalls, and substance identifiers.
Streamlines the creation, testing, and optimization of sophisticated autonomous agents and subagents within the Claude Code ecosystem.
Orchestrates over 600 scientific tools and datasets for bioinformatics, drug discovery, and advanced computational research workflows.
Generates publication-quality charts and statistical visualizations using Matplotlib and Seaborn.
Automates the configuration and management of reproducible data collection pipelines from databases, APIs, web scraping, and LLM generation.
Exports data analysis results into multiple professional formats including CSV, Excel, JSON, and Markdown with customized formatting.
Executes complex, multi-step biomedical research tasks using autonomous AI reasoning and integrated biological databases.
Explores datasets and generates interactive visualizations in marimo notebooks using Polars and Plotly Graph Objects.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical data analysis using an autonomous agent framework.
Executes autonomous multi-step research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Automates the end-to-end scientific research pipeline from hypothesis generation to publication-ready LaTeX manuscripts.
Accesses the NIH Metabolomics Workbench API to retrieve experimental study data, metabolite structures, and standardized biochemical nomenclature.
Accesses the NIH Metabolomics Workbench to query metabolite structures, experimental studies, and mass spectrometry data.
Assists medical professionals by extracting symptoms from natural language, identifying potential diagnoses, and suggesting clinical next steps.
Applies medicinal chemistry rules, structural alerts, and drug-likeness filters to prioritize compound libraries for drug discovery.
Performs exact symbolic mathematical computations including algebra, calculus, and physics modeling directly in Python.
Manipulates, analyzes, and visualizes phylogenetic and hierarchical trees with seamless NCBI taxonomy integration.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant associations, trait data, and genomic summary statistics.
Conducts systematic, comprehensive literature reviews across multiple scientific databases with verified citations and professional formatting.
Connects Claude to the ZINC22 database to perform chemical compound searches, virtual screening, and drug discovery workflows.
Migrates codebases and prompts from Claude Sonnet 4.0, 4.5, or Opus 4.1 to the Opus 4.5 model across multiple platforms.
Generates, edits, and analyzes complex Excel workbooks using dynamic formulas, professional financial formatting, and automated data validation.
Automates end-to-end scientific research workflows from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
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