Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Analyzes single-cell omics data using deep generative models for batch correction, multi-omic integration, and probabilistic modeling.
Performs advanced time series machine learning tasks including classification, forecasting, and anomaly detection using scikit-learn compatible APIs.
Performs comprehensive bioinformatics analysis including sequence manipulation, phylogenetics, and microbial ecology statistics within Python.
Accelerates genomic interval analysis and machine learning preprocessing using a high-performance Rust toolkit with Python bindings.
Detects system hardware capabilities and provides optimized computational strategies for scientific and data-intensive tasks.
Empowers Claude to create, analyze, and format professional Excel spreadsheets and financial models with automated formula recalculation.
Generates publication-quality scientific diagrams, neural network architectures, and flowcharts using specialized Python libraries.
Accesses the Reactome database to perform biological pathway analysis, gene mapping, and enrichment studies for systems biology.
Facilitates programmatic access to the ClinicalTrials.gov API v2 for advanced trial discovery, patient matching, and medical research data extraction.
Builds and deploys production-grade bioinformatics pipelines as serverless workflows on the Latch platform.
Facilitates creative scientific problem-solving by generating hypotheses and exploring interdisciplinary connections as a research ideation partner.
Searches and retrieves life sciences preprints from the bioRxiv database by keywords, authors, and categories.
Accesses and analyzes over 240 million scholarly works, authors, and institutions via the OpenAlex API for automated scientific discovery.
Empowers Claude to perform graph-based drug discovery, molecular property prediction, and protein modeling using the TorchDrug framework.
Access and retrieve comprehensive nucleotide sequence data and metadata from the European Nucleotide Archive (ENA).
Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Enables advanced searching and programmatic retrieval of biomedical literature from the PubMed database using E-utilities and MeSH terms.
Provides comprehensive tools for materials analysis, crystal structure manipulation, and Materials Project database integration.
Accesses, searches, and retrieves gene expression and functional genomics data from the NCBI Gene Expression Omnibus (GEO).
Analyzes and visualizes complex graph data structures using the comprehensive Python NetworkX library.
Integrates comprehensive pharmaceutical data from DrugBank for drug discovery, pharmacology research, and safety analysis.
Processes and analyzes complex mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Generates professional, publication-ready clinical decision support documents and biomarker-stratified cohort analyses in LaTeX format.
Manages and analyzes annotated data matrices for single-cell genomics and large-scale biological datasets.
Processes and analyzes high-throughput sequencing data to generate publication-quality genomic visualizations and quality control reports.
Retrieves genomic, proteomic, and structural data from over 20 biological databases using a unified interface.
Applies medicinal chemistry filters and drug-likeness rules to prioritize compound libraries for autonomous discovery.
Accelerates high-performance data analysis and manipulation using the lightning-fast Polars DataFrame library.
Processes and analyzes massive tabular datasets exceeding available RAM using lazy, out-of-core DataFrame operations.
Performs exact symbolic mathematics in Python, including algebraic solving, calculus, and matrix manipulations.
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