Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Generates professional, publication-quality statistical graphics and complex multi-panel data visualizations using Python's Seaborn library.
Facilitates advanced probabilistic modeling and analysis of single-cell omics data using deep generative models.
Analyzes mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Streamlines machine learning workflows in Python by providing expert guidance on scikit-learn algorithms, data preprocessing, and production-ready pipelines.
Processes and prepares whole slide pathology images for deep learning and digital pathology workflows.
Develops high-performance reinforcement learning systems with optimized PPO training, vectorized simulations, and multi-agent support.
Automates laboratory workflows and controls liquid handling robots, plate readers, and analytical equipment through a unified Python interface.
Streamlines the design and architecture of domain-specific AI agents using Claude Agent SDK patterns.
Automates biomedical literature searches and data retrieval from the PubMed database using advanced MeSH queries and the E-utilities API.
Provides a comprehensive suite of statistical modeling tools for rigorous inference, hypothesis testing, and econometric analysis in Python.
Integrates Hugging Face Transformers for advanced natural language processing, computer vision, and audio tasks within development workflows.
Simplifies querying the openFDA API to analyze regulatory data, drug safety profiles, medical device clearances, and food recalls.
Accesses the Human Metabolome Database (HMDB) to retrieve metabolite data, chemical properties, and clinical biomarkers for metabolomics research.
Queries the NHGRI-EBI GWAS Catalog to retrieve SNP-trait associations, genetic variant data, and genome-wide association study summary statistics.
Enables development and training of Graph Neural Networks (GNNs) using the PyTorch Geometric library.
Searches and retrieves life sciences preprints from the bioRxiv database with advanced filtering and PDF download capabilities.
Connects Claude to cloud laboratory services for automated protein testing, sequence optimization, and wet-lab validation.
Streamlines genomics pipeline development and data management on the DNAnexus cloud platform using the dxpy Python SDK.
Accesses and analyzes global public statistical data through the Data Commons knowledge graph and Python API.
Generates testable, evidence-based scientific hypotheses and experimental designs across multiple research domains.
Performs high-performance genomic interval analysis, overlap detection, and machine learning tokenization using Rust-powered tools.
Enables programmatic PDF manipulation, data extraction, and document creation using professional Python and command-line tools.
Automates professional Excel spreadsheet creation, financial modeling, and data analysis with error-free formula verification.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Provides a unified interface for rapid bioinformatics queries across 20+ genomic databases including Ensembl, AlphaFold, and NCBI.
Trains and deploys complex neural network architectures within distributed E2B sandbox environments using Flow Nexus.
Queries and analyzes the OpenAlex database to search scholarly literature, track citations, and perform bibliometric analysis.
Creates, modifies, and analyzes professional Excel spreadsheets with automated formula recalculation and industry-standard financial formatting.
Empowers protein engineering and biological research through state-of-the-art ESM3 generative models and ESM C embeddings.
Explains machine learning model predictions and feature importance using mathematically grounded Shapley values and high-impact visualizations.
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