Descubre Habilidades de Claude para data science & ml. Explora 53 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Accesses the KEGG REST API to perform biological pathway analysis, gene mapping, and molecular interaction research.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic abstraction layer over RDKit.
Accesses and analyzes over 61 million standardized single-cell genomics records from the CZ CELLxGENE Discover census.
Generates journal-ready scientific figures and multi-panel layouts following publication-quality standards.
Automates laboratory workflows by writing and simulating Opentrons Python Protocol API v2 for Flex and OT-2 robots.
Evaluates research rigor, methodology, and statistical validity using standardized frameworks like GRADE and Cochrane ROB.
Processes and analyzes high-throughput sequencing data to generate publication-quality genomic visualizations and quality control reports.
Integrates Hugging Face Transformers to load, fine-tune, and run inference on thousands of pre-trained AI models across multiple modalities.
Empowers Claude to perform graph-based drug discovery, molecular property prediction, and protein modeling using the TorchDrug framework.
Accesses and analyzes 3D protein and nucleic acid structures from the RCSB Protein Data Bank for structural biology and drug discovery.
Manages and analyzes annotated data matrices for single-cell genomics and large-scale biological datasets.
Queries the NCBI Gene database to retrieve comprehensive genetic information, sequences, and functional annotations for biological research.
Accesses and analyzes comprehensive USPTO patent and trademark data for intellectual property research and prior art discovery.
Queries the NCBI ClinVar database to retrieve, interpret, and process human genetic variant clinical significance data.
Automates scientific hypothesis generation and empirical testing by synthesizing observational data with research literature.
Provides programmatic access to over 40 bioinformatics web services for automated biological data retrieval and pathway analysis.
Implements comprehensive machine learning workflows using scikit-learn, covering data preprocessing, model training, evaluation, and pipeline deployment.
Performs rigorous statistical modeling and econometric analysis using regression, time series, and diagnostic testing.
Researches academic literature, technical documentation, and scientific data with automatic model selection and citation support.
Automates laboratory equipment and workflows using a hardware-agnostic Python interface for liquid handlers, plate readers, and more.
Accelerates high-performance data analysis and manipulation using the lightning-fast Polars DataFrame library.
Accesses the world's leading protein sequence and functional information resource via the UniProt REST API.
Analyzes and visualizes phylogenetic trees with support for evolutionary event detection and NCBI taxonomy integration.
Facilitates creative scientific problem-solving by generating hypotheses and exploring interdisciplinary connections as a research ideation partner.
Provides comprehensive Python tools for biological computation, sequence analysis, and bioinformatics database access.
Creates publication-quality statistical graphics and exploratory data visualizations using a high-level Python interface.
Accesses and integrates the world's most comprehensive database for exploring somatic mutations in human cancer into bioinformatics workflows.
Conducts systematic, rigorous reviews of scientific manuscripts and grant proposals by evaluating methodology, statistics, and reporting standards.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant associations, study metadata, and polygenic risk score data.
Queries the Open Targets Platform to identify and prioritize therapeutic drug targets using genetic, omic, and clinical evidence.
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