data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Automates end-to-end scientific research workflows from data analysis and hypothesis generation to producing publication-ready LaTeX papers.
Generates professional, multi-page PDF reports with formatted tables, text, and embedded data visualizations using the reportlab library.
Generates professional, publication-quality plots and data visualizations using Python's foundational plotting library.
Automates Excel spreadsheet manipulation, data analysis, and professional reporting using Python-based data science libraries.
Access and analyze NCBI Gene Expression Omnibus (GEO) data for transcriptomics and functional genomics research.
Queries the openFDA API to retrieve and analyze data on drugs, medical devices, food safety, and adverse events.
Analyzes single-cell omics data using deep generative models for batch correction, integration, and differential expression.
Accesses over 600 scientific tools and databases for bioinformatics, drug discovery, and computational biology research.
Accesses over 40 bioinformatics web services and databases through a unified Python interface for biological data retrieval and analysis.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering.
Infers gene regulatory networks from transcriptomics data using scalable GRNBoost2 and GENIE3 algorithms.
Simplifies complex molecular informatics workflows by providing a Pythonic interface for RDKit with sensible defaults and built-in parallelization.
Simplifies molecular cheminformatics and drug discovery workflows with a Pythonic abstraction layer over RDKit.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Builds discrete-event simulation models in Python to analyze complex systems involving queues, resources, and time-based processes.
Develops, tests, and deploys machine learning models for clinical healthcare data using standardized pipelines and specialized medical architectures.
Integrates managed vector databases into AI applications for production-grade RAG, semantic search, and recommendation systems.
Analyzes high-throughput sequencing data to perform quality control, normalization, and publication-quality visualization for NGS experiments.
Simulates and analyzes genome-scale metabolic models using constraint-based reconstruction and analysis (COBRA) techniques.
Builds process-based discrete-event simulations in Python for modeling complex systems like logistics, manufacturing, and networks.
Executes complex autonomous research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Accesses the European Nucleotide Archive (ENA) to retrieve genomic sequences, raw reads, and metadata for bioinformatics pipelines.
Builds, simulates, and executes quantum circuits using Google’s open-source framework for NISQ-era quantum computers.
Analyzes Excel spreadsheets, generates pivot tables, and creates data visualizations using Python libraries like pandas and openpyxl.
Searches the arXiv preprint repository for scholarly articles across various scientific and technical domains.
Streamlines computational molecular biology tasks including sequence analysis, NCBI database integration, and structural protein modeling.
Searches the arXiv preprint repository for scholarly articles in computer science, physics, mathematics, and quantitative biology.
Generates interactive, publication-quality data visualizations and dashboards using the Plotly Python library.
Access over 40 bioinformatics web services and databases including UniProt, KEGG, and ChEMBL through a unified Python interface.
Automates protein sequence optimization and experimental validation through cloud-based laboratory testing.
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