Discover Agent Skills for data science & ml. Browse 53skills for Claude, ChatGPT & Codex.
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto front analysis.
Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publishing LaTeX-formatted papers.
Applies medicinal chemistry filters and drug-likeness rules to prioritize compound libraries for autonomous discovery.
Provides AI-ready datasets and benchmarks for therapeutic machine learning and drug discovery tasks.
Accesses and analyzes comprehensive FDA regulatory data for drugs, medical devices, and food safety through the openFDA API.
Processes and analyzes complex mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering.
Builds and deploys specialized machine learning models for clinical healthcare data and electronic health records.
Automates scientific hypothesis generation and empirical testing by synthesizing observational data with research literature.
Explains machine learning model predictions and feature importance using Shapley Additive exPlanations for transparent and interpretable AI.
Analyzes and visualizes complex graph data structures using the comprehensive Python NetworkX library.
Parses and manipulates Flow Cytometry Standard (FCS) files for scientific data preprocessing and analysis.
Manipulates genomic datasets by reading and writing SAM, BAM, CRAM, VCF, and FASTA files using a Pythonic interface.
Retrieves genomic, proteomic, and structural data from over 20 biological databases using a unified interface.
Builds and validates advanced Bayesian probabilistic models using PyMC 5.x for scientific discovery and statistical inference.
Accelerates genomic interval analysis and machine learning preprocessing using a high-performance Rust toolkit with Python bindings.
Performs comprehensive bioinformatics analysis including sequence manipulation, phylogenetics, and microbial ecology statistics within Python.
Performs advanced time series machine learning tasks including classification, forecasting, and anomaly detection using scikit-learn compatible APIs.
Analyzes single-cell omics data using deep generative models for batch correction, multi-omic integration, and probabilistic modeling.
Performs automated differential gene expression analysis on bulk RNA-seq data using the PyDESeq2 framework.
Predicts accurate 3D protein-ligand binding poses using diffusion-based deep learning for computational drug discovery.
Provides comprehensive cheminformatics capabilities for molecular analysis, manipulation, and property calculation within Claude Code.
Analyzes whole-slide images and multiparametric imaging data for advanced computational pathology and machine learning workflows.
Scales Python data science workflows using parallel and distributed computing for larger-than-memory datasets.
Generates professional, publication-ready clinical decision support documents and biomarker-stratified cohort analyses in LaTeX format.
Manages biological datasets with automated lineage tracking, ontology-based curation, and FAIR-compliant data lakehouse capabilities.
Executes complex biomedical research tasks across genomics, drug discovery, and clinical analysis using autonomous AI reasoning.
Facilitates creative scientific problem-solving by generating hypotheses and exploring interdisciplinary connections as a research ideation partner.
Performs comprehensive single-cell RNA-seq data analysis, including quality control, clustering, and visualization.
Empowers Claude to design, generate, and analyze protein sequences and structures using ESM3 and ESM C evolutionary scale models.
Scroll for more results...