Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Generates high-performance text embeddings for RAG systems, semantic search, and document clustering using the Gemini API.
Generates and tests scientific hypotheses from observational datasets and research literature using automated LLM frameworks.
Queries and interprets NCBI ClinVar data to identify the clinical significance of human genetic variants.
Facilitates deep analysis and navigation of the AgentScope library to assist in building multi-agent systems.
Accesses and retrieves nucleotide sequence data, raw reads, and genome assemblies from the European Nucleotide Archive (ENA).
Empowers Claude to create, train, and deploy self-learning autonomous agents using nine specialized reinforcement learning algorithms.
Streamlines deep learning workflows by organizing PyTorch code into scalable, modular structures for multi-GPU and TPU training.
Automates life sciences R&D workflows by integrating with the Benchling platform for inventory management, registry entities, and electronic lab notebooks.
Automates the gathering, normalization, and verification of large-scale research paper datasets for evidence-based surveys.
Automates laboratory data management and R&D workflows by integrating with Benchling's registry, inventory, and electronic lab notebook systems.
Automates life sciences research workflows by integrating Benchling's registry, inventory, and electronic lab notebook via Python SDK and API.
Calculates and interprets key financial ratios and performance metrics from corporate financial statements to support investment analysis.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical analysis through autonomous agent reasoning.
Automates end-to-end scientific research workflows from hypothesis generation and data analysis to publication-ready LaTeX papers.
Enables advanced biological computation and molecular biology workflows using the Biopython library.
Automates end-to-end scientific research workflows from initial data analysis to publication-ready LaTeX manuscripts.
Automates the end-to-end scientific research lifecycle from data hypothesis generation to publication-ready LaTeX manuscripts.
Provides programmatic Python access to over 40 bioinformatics web services and databases for integrated biological data analysis.
Accesses and integrates over 40 bioinformatics web services and databases through a unified Python interface.
Implements high-performance semantic vector search and intelligent document retrieval for Claude-powered RAG systems.
Generates standardized PyTorch docstrings following official Sphinx and reStructuredText conventions for deep learning projects.
Executes autonomous multi-step biomedical research tasks spanning genomics, drug discovery, and clinical analysis.
Streamlines biomedical data analysis and genomics pipeline development on the DNAnexus cloud platform.
Builds advanced financial models including DCF analysis, Monte Carlo simulations, and sensitivity testing for data-driven investment decisions.
Analyzes high-throughput sequencing data (NGS) through automated quality control, normalization, and publication-quality visualization.
Provides programmatic access to DrugBank's extensive bio- and cheminformatics data for pharmaceutical research and drug discovery.
Queries the ClinicalTrials.gov API v2 to search, filter, and export global clinical study data for medical research and patient matching.
Generates sophisticated financial models including DCF analysis, Monte Carlo simulations, and risk assessments for investment decision-making.
Migrates codebase references, API calls, and prompts from previous Claude models to the Opus 4.5 architecture.
Manages systematic literature screening by evaluating titles and abstracts against formal research protocols to generate auditable logs.
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