Claude Scientific Skills
A comprehensive collection of 70+ ready-to-use scientific skills curated by K-Dense AI that transforms Claude Code into an "AI Scientist" with access to specialized scientific libraries, databases, and research tools.
Overview
This repository enables Claude to work with cutting-edge scientific tools across multiple domains including bioinformatics, cheminformatics, proteomics, machine learning, materials science, and data analysis.
Skills Collection
Scientific Databases (24 skills)
Access major scientific databases including:
- Genomics & Proteomics: PubMed, UniProt, AlphaFold DB
- Drug Discovery: PubChem, ChEMBL, DrugBank
- Clinical Research: COSMIC, ClinVar, GTEx
- And many more specialized databases
Scientific Packages (41 skills)
Work with specialized scientific libraries:
- Bioinformatics: BioPython, Scanpy, PyMOL
- Cheminformatics: RDKit, DeepChem, Open Babel
- Machine Learning: PyTorch, scikit-learn, TensorFlow
- Materials Science: ASE, Pymatgen, VASP tools
Scientific Thinking & Analysis
Advanced research capabilities:
- Exploratory data analysis
- Hypothesis generation
- Peer review frameworks
- Scientific writing assistance
- Document processing
Scientific Integrations (6 platforms)
Connect with lab management and automation:
- Benchling
- DNAnexus
- Opentrons
- LabArchives
- LatchBio
- OMERO
Use Cases
- Drug Discovery: Screen compounds, analyze molecular properties, predict binding
- Genomics Research: Analyze sequences, process NGS data, annotate genomes
- Proteomics: Study protein structures, predict interactions, analyze expression
- Materials Science: Design materials, calculate properties, run simulations
- Clinical Research: Analyze patient data, investigate mutations, study disease genes
- Academic Research: Literature review, data analysis, hypothesis testing
Who It's For
- Computational biologists and bioinformaticians
- Medicinal chemists and drug discovery researchers
- Academic researchers across life sciences
- Data scientists working in scientific domains
- Materials scientists and chemical engineers
- Anyone building AI-powered scientific tools
Domains Covered
- Genomics: Sequence analysis, gene expression, variant calling
- Drug Discovery: Compound screening, ADMET prediction, target identification
- Proteomics: Protein structure, function prediction, interactions
- Clinical Research: Disease genetics, biomarker discovery, patient data
- Materials Science: Crystal structures, property prediction, simulations
- Academic Research: Literature analysis, data visualization, statistics
Getting Started
These skills are designed to work with Claude Code and can be easily integrated into your scientific workflows. Each skill includes detailed documentation on usage, parameters, and example workflows.
Project Background
Created by K-Dense AI, a company building autonomous AI scientists for scientific research. These skills represent real-world tools and workflows used in cutting-edge scientific discovery.
For questions or collaboration: orion.li@k-dense.ai