Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Facilitates programmatic access to the ClinicalTrials.gov API v2 to search, filter, and export global clinical study data for research and patient matching.
Accesses and analyzes comprehensive FDA regulatory data for drugs, medical devices, and food safety through the openFDA API.
Manages large-scale N-dimensional arrays with chunking, compression, and cloud-native storage integration.
Automates electronic lab notebook management through the LabArchives REST API for research documentation, data backups, and tool integration.
Generates publication-quality scientific diagrams and architectural schematics using AI-driven iterative refinement and quality auditing.
Facilitates advanced biomedical literature research and programmatic access to the PubMed database using E-utilities and complex query syntax.
Generates interactive, publication-quality scientific and statistical visualizations using the Plotly Python library.
Facilitates advanced Bayesian statistical modeling and probabilistic programming using the PyMC and ArviZ ecosystems.
Empowers molecular machine learning and drug discovery through advanced chemical featurization, property prediction, and Graph Neural Networks.
Parses and manages Flow Cytometry Standard (FCS) files, enabling seamless conversion to NumPy arrays and metadata extraction for bioinformatics workflows.
Extends pandas to enable powerful spatial operations and vector data analysis for complex geographic workflows.
Builds, analyzes, and visualizes complex network structures and graph algorithms using Python's NetworkX library.
Enables building, training, and optimizing quantum circuits and hybrid quantum-classical models using automatic differentiation and hardware-agnostic execution.
Accelerates data analysis workflows using Polars' lightning-fast, expression-based API and lazy evaluation framework.
Accelerates and scales Python data processing by providing parallel and distributed computing capabilities for NumPy, pandas, and custom workflows.
Performs differential gene expression analysis on bulk RNA-seq data using Python's DESeq2 implementation.
Generates publication-quality scientific plots and data visualizations using Python's foundational plotting library.
Simplifies molecular cheminformatics and drug discovery workflows with a Pythonic abstraction layer for RDKit.
Simulates high-performance computational fluid dynamics using pseudospectral methods and Python-based solvers.
Solves complex multi-objective optimization problems using evolutionary algorithms to find Pareto-optimal solutions.
Filters and prioritizes molecular libraries using medicinal chemistry rules, structural alerts, and drug-likeness metrics.
Simplifies molecular featurization for machine learning by providing a unified interface for over 100 descriptors, fingerprints, and pretrained embeddings.
Predicts 3D protein-ligand binding poses and confidence scores using state-of-the-art diffusion models for structure-based drug design.
Performs high-performance genomic interval analysis and sequence tokenization using Rust-powered tools and Python bindings.
Processes and analyzes mass spectrometry data using advanced spectral similarity metrics and automated metadata harmonization.
Analyzes crystal structures, generates phase diagrams, and integrates with the Materials Project for advanced computational materials science.
Manipulates, analyzes, and visualizes phylogenetic trees and hierarchical data using the Environment for Tree Exploration (ETE) framework.
Simplifies bioinformatics workflows by providing unified access to over 20 genomic and proteomic databases for sequence analysis and protein modeling.
Facilitates comprehensive Next-Generation Sequencing (NGS) data processing, quality control, and publication-quality visualization.
Connects Claude to the Adaptyv cloud laboratory platform for automated protein design validation and experimental testing.
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