Explore our collection of Agent Skills to enhance your AI workflow.
Scales Python data processing and scientific computing across multiple cores or distributed clusters for larger-than-RAM datasets.
Accesses and analyzes comprehensive FDA regulatory data for drugs, medical devices, food safety, and substances through the openFDA API.
Provides programmatic access to openFDA datasets for drug safety research, medical device surveillance, and food recall analysis.
Accesses and analyzes comprehensive FDA regulatory data for drugs, medical devices, and food safety through the openFDA API.
Empowers drug discovery and molecular analysis by integrating the DeepChem toolkit for property prediction, featurization, and graph neural networks.
Facilitates molecular machine learning, property prediction, and drug discovery workflows using the DeepChem library.
Streamlines molecular machine learning workflows for drug discovery, property prediction, and graph neural network implementation.
Streamlines the development, deployment, and management of bioinformatics applications and data workflows on the DNAnexus cloud genomics platform.
Accesses and analyzes comprehensive pharmaceutical data from the DrugBank database for drug discovery and pharmacology research.
Enables advanced protein engineering, sequence generation, and structure prediction using Evolutionary Scale Modeling.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to the production of publication-ready LaTeX manuscripts.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to the production of publication-ready LaTeX manuscripts.
Automates end-to-end scientific research workflows from initial data analysis to publication-ready LaTeX manuscripts.
Automates scientific hypothesis generation and testing by combining observational data with literature-based insights using large language models.
Predicts 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug design.
Predicts 3D protein-ligand binding poses using state-of-the-art diffusion models for structure-based drug discovery.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug design.
Predicts high-accuracy 3D binding poses of small molecule ligands to protein targets using state-of-the-art diffusion models.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug discovery.
Analyzes hardware capabilities and provides strategic recommendations for computationally intensive scientific tasks.
Detects and reports system hardware capabilities to provide optimized strategies for data science and intensive computing tasks.
Detects and reports available system hardware resources to provide strategic recommendations for computationally intensive tasks.
Facilitates the development and management of genomics pipelines on the DNAnexus cloud platform using the dxpy Python SDK and CLI.
Enables professional-grade spreadsheet creation, formula-driven financial modeling, and data analysis with automated error validation.
Automates PDF document manipulation including text extraction, merging, splitting, and programmatic creation.
Accesses and queries the NCBI Gene database to retrieve comprehensive genetic information, sequences, and functional annotations via E-utilities and Datasets APIs.
Queries NCBI Gene databases to retrieve comprehensive genomic data, including sequences, annotations, and functional pathways.
Transforms academic papers from LaTeX or PDF into interactive websites, professional presentation videos, and print-ready conference posters.
Empowers protein research and design using state-of-the-art ESM3 and ESM C language models for sequence generation, structure prediction, and representation learning.
Accesses the Human Metabolome Database to retrieve metabolite properties, clinical biomarker data, and spectral information for metabolomics research.
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