Explora nuestra colección completa de Habilidades de Claude que extienden las capacidades de los agentes de IA.
Implements comprehensive machine learning workflows using scikit-learn for classification, regression, clustering, and data preprocessing.
Generates publication-quality statistical graphics and complex data visualizations using the Seaborn Python library.
Performs professional statistical modeling, hypothesis testing, and rigorous assumption verification with publication-ready APA reporting.
Generates interactive, publication-quality scientific and statistical charts using the Plotly Python library.
Streamlines biomedical data management and genomics workflow automation on the DNAnexus cloud platform.
Programmatically creates, edits, and analyzes PowerPoint presentations with support for scientific schematics and XML-level customization.
Generates visually stunning, research-backed scientific presentations and conference slides with automated image generation and citation management.
Accesses the ClinicalTrials.gov API v2 to search, filter, and export clinical study data for medical research and patient matching.
Streamlines high-density neural recording analysis, spike sorting, and quality metric computation for Neuropixels electrophysiology data.
Performs comprehensive single-cell RNA-seq analysis workflows including quality control, normalization, clustering, and cell-type annotation.
Integrates NCBI Gene data access into Claude for querying sequences, functional annotations, and genomic metadata.
Enables advanced materials science research through crystal structure manipulation, thermodynamic analysis, and Materials Project database integration.
Accesses and analyzes over 200 million AI-predicted protein structures from the AlphaFold DB for structural biology and drug discovery.
Generates professional, publication-quality scientific research posters using LaTeX frameworks like beamerposter, tikzposter, and baposter.
Accesses the NIH Metabolomics Workbench to query over 4,200 studies, standardize metabolite nomenclature, and perform mass spectrometry searches.
Integrates the Reactome database to perform pathway enrichment, gene-pathway mapping, and molecular interaction analysis for systems biology.
Manipulates PDF documents by extracting text and tables, merging or splitting files, and generating new documents programmatically.
Predicts high-accuracy 3D protein-ligand binding poses using state-of-the-art diffusion-based deep learning models.
Accesses and analyzes the Ensembl REST API for gene lookups, sequence retrieval, and advanced variant effect predictions in genomic research.
Streamlines deep learning development by organizing PyTorch code into scalable, boilerplate-free LightningModules and automated training workflows.
Crafts competitive, agency-compliant research proposals for major federal funding bodies like the NSF, NIH, DOE, and DARPA.
Generates regulatory-compliant clinical reports and medical documentation with integrated scientific visualizations.
Enables programmatic access to the RCSB Protein Data Bank for searching, retrieving, and analyzing 3D structures of biological macromolecules.
Generates professional-grade scientific plots and data visualizations using Python's foundational Matplotlib library.
Processes and analyzes mass spectrometry data using the Matchms library for spectral similarity and metadata harmonization.
Accesses the world's largest chemical database to search compounds, retrieve molecular properties, and perform structure-based searches.
Accesses the world's most comprehensive enzyme database to retrieve kinetic parameters, reaction equations, and biochemical property data.
Simulates high-performance computational fluid dynamics using pseudospectral methods and Python-based analysis.
Accesses and analyzes over 61 million standardized single-cell genomics records from the CZ CELLxGENE Census.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering tasks.
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