Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Processes and analyzes physiological signals like ECG, EEG, and EDA using the NeuroKit2 Python library.
Automates Next-Generation Sequencing (NGS) data processing, quality control, and publication-quality visualization.
Infers gene regulatory networks from transcriptomics data using scalable GRNBoost2 and GENIE3 algorithms.
Automates scientific hypothesis generation and testing by combining observational data with research literature using large language models.
Queries the NCBI Gene database to retrieve comprehensive genetic information, metadata, and sequences for annotation and functional analysis.
Analyzes and visualizes complex network structures and graph data using the Python NetworkX library.
Simplifies astronomical data processing and astrophysical calculations using the core Python Astropy library.
Streamlines the development, deployment, and management of bioinformatics applications and data workflows on the DNAnexus cloud genomics platform.
Queries NCBI Gene databases to retrieve comprehensive genomic data, including sequences, annotations, and functional pathways.
Simplifies complex molecular informatics workflows by providing a Pythonic interface for RDKit with sensible defaults and built-in parallelization.
Facilitates advanced astronomical research and data processing through Python-based coordinate transforms, FITS manipulation, and cosmological modeling.
Simplifies molecular cheminformatics and drug discovery workflows with a Pythonic abstraction layer over RDKit.
Develops, deploys, and manages genomics pipelines and biomedical data on the DNAnexus cloud platform.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Processes and generates multimedia content including audio, video, images, and documents using the Google Gemini API.
Provides specialized tools for biological computation, sequence analysis, and programmatic access to NCBI databases using Biopython.
Builds discrete-event simulation models in Python to analyze complex systems involving queues, resources, and time-based processes.
Builds and optimizes complex discrete-event simulations using the SimPy framework for Python.
Develops, tests, and deploys machine learning models for clinical healthcare data using standardized pipelines and specialized medical architectures.
Provides unified access to 20+ genomic databases for sequence analysis, protein structure prediction, and rapid bioinformatics queries.
Integrates managed vector databases into AI applications for production-grade RAG, semantic search, and recommendation systems.
Analyzes high-throughput sequencing data to perform quality control, normalization, and publication-quality visualization for NGS experiments.
Simulates and analyzes genome-scale metabolic models using constraint-based reconstruction and analysis (COBRA) techniques.
Automates tissue detection and tile extraction from gigapixel histopathology images for computational pathology deep learning pipelines.
Interfaces with the European Nucleotide Archive to programmatically retrieve DNA/RNA sequences, raw reads, and genome metadata.
Builds process-based discrete-event simulations in Python for modeling complex systems like logistics, manufacturing, and networks.
Predicts 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug design.
Executes complex autonomous research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Access and query the world's largest database of somatic mutations and cancer genomics data for precision oncology research.
Empowers protein research and design using state-of-the-art ESM3 and ESM C language models for sequence generation, structure prediction, and representation learning.
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