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-ready clinical decision support documents, biomarker-stratified cohort analyses, and evidence-based treatment guidelines.
Queries and interprets NCBI ClinVar data to evaluate genetic variant pathogenicity and clinical significance for genomic medicine.
Performs constraint-based metabolic modeling and systems biology simulations using the COBRApy framework.
Generates publication-quality scientific diagrams and neural network architectures with AI-powered quality review.
Accesses and queries the Catalogue of Somatic Mutations in Cancer (COSMIC) for precision oncology and genomic research.
Facilitates direct REST API access to the KEGG database for bioinformatics research, pathway analysis, and gene mapping.
Queries the Open Targets Platform to identify and prioritize therapeutic drug targets through genetic, omics, and clinical evidence.
Facilitates drug discovery and therapeutic machine learning by providing AI-ready datasets, benchmarks, and molecular evaluation oracles.
Scales Python, pandas, and NumPy workflows across multiple cores or clusters for larger-than-memory datasets.
Accesses and queries global statistical data from Data Commons to provide programmatic insights into demographics, economics, and environmental indicators.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for drug discovery, pharmacology research, and safety analysis.
Simplifies molecular cheminformatics workflows by providing a Pythonic wrapper around RDKit with sensible defaults and parallel processing.
Generates interactive, publication-quality scientific and statistical charts using Plotly Express and Graph Objects.
Processes and analyzes genomic datasets including SAM, BAM, VCF, and FASTA files using a Pythonic interface to htslib.
Facilitates molecular machine learning and drug discovery workflows using the DeepChem toolkit.
Enables building, training, and optimizing quantum circuits and hybrid quantum-classical machine learning models with automatic differentiation.
Retrieves and analyzes protein-protein interaction networks and functional enrichment data directly from the STRING database.
Integrates Claude with the DNAnexus cloud genomics platform to develop bioinformatics pipelines, manage data, and orchestrate workflows.
Processes and analyzes mass spectrometry data using Python for metabolomics and chemical identification.
Processes, modifies, and analyzes DICOM medical imaging files using the pydicom library.
Queries the Ensembl REST API to retrieve gene annotations, sequences, variants, and comparative genomic data for over 250 species.
Manipulates, analyzes, and visualizes phylogenetic trees with advanced support for evolutionary event detection and NCBI taxonomy integration.
Integrates with the NCBI Gene Expression Omnibus (GEO) to search, download, and analyze high-throughput functional genomics datasets.
Builds and deploys bioinformatics workflows using the Latch SDK and serverless cloud infrastructure.
Performs comprehensive exploratory data analysis on over 200 scientific file formats to generate detailed quality reports and statistical summaries.
Queries and analyzes openFDA data for drugs, medical devices, food safety, and adverse events using a standardized Python interface.
Performs robust differential gene expression analysis for bulk RNA-seq data using the Python implementation of DESeq2.
Simulates complex fluid dynamics using high-performance Python pseudospectral methods and solvers for Navier-Stokes and geophysical flows.
Queries the NCBI Gene database to retrieve comprehensive genomic information, including sequences, annotations, and functional data.
Extends pandas with geometric operations and spatial data structures for advanced geospatial analysis and mapping.
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