浏览所有 Claude 技能

Single-Cell Omics Analysis (scvi-tools)

Analyzes single-cell omics data using deep generative models for batch correction, multimodal integration, and differential expression.

NCBI Gene Database Explorer

Queries and retrieves comprehensive gene information from NCBI databases for genomic research and functional analysis.

Molfeat Molecular Featurization

Converts chemical structures into high-quality numerical features for molecular machine learning and cheminformatics tasks.

TorchDrug Molecular Science

Accelerates drug discovery and molecular research using graph neural networks and PyTorch-based machine learning.

OMERO Microscopy Integration

Manages microscopy data and metadata via the OMERO Python API for scientific imaging and high-content screening workflows.

GEO Database Explorer

Accesses and analyzes functional genomics data from the NCBI Gene Expression Omnibus (GEO) repository.

Zarr Python Scientific Data

Manage large-scale N-dimensional arrays with chunking, compression, and cloud-native storage for scientific computing workflows.

Scikit-learn Machine Learning

Implements professional machine learning workflows in Python using scikit-learn for classification, regression, clustering, and data preprocessing.

Scanpy Single-Cell Analysis

Performs comprehensive single-cell RNA-seq analysis workflows including quality control, clustering, and trajectory inference.

Arboreto Gene Regulatory Network Inference

Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.

Biopython Bioinformatics Toolkit

Automates computational molecular biology tasks including sequence manipulation, NCBI database queries, and structural analysis.

PyMC Bayesian Modeling

Build, fit, and validate complex Bayesian probabilistic models using the PyMC Python library and modern MCMC sampling techniques.

Denario Scientific Research Assistant

Automates the end-to-end scientific research lifecycle from initial data hypothesis to publication-ready LaTeX manuscripts.

Hypogenic Scientific Discovery

Automates the generation and testing of scientific hypotheses by synthesizing empirical data and existing research literature.

PyHealth AI Toolkit

Develops and deploys specialized machine learning models for clinical healthcare tasks using electronic health records, medical coding, and physiological data.

PufferLib RL Performance

Accelerates reinforcement learning workflows with high-performance training, optimized environment vectorization, and seamless multi-agent support.

ReportLab PDF Automation

Generates professional, programmatic PDF documents including reports, invoices, and data-driven charts using Python.

Dask Parallel Computing

Enables parallel and distributed computing in Python to scale pandas and NumPy workflows across multiple cores or clusters for larger-than-memory datasets.

DiffDock Molecular Docking

Predicts 3D protein-ligand binding poses using state-of-the-art diffusion-based deep learning for drug discovery.

Scientific Manuscript Writing

Streamlines the creation of professional research papers using IMRAD structure, standard citation styles, and reporting guidelines.

ZINC Database Integration

Accesses the ZINC22 database to search, filter, and retrieve over 230 million purchasable chemical compounds for drug discovery.

Astropy Scientific Computing

Performs advanced astronomical data analysis, coordinate transformations, and cosmological calculations using the core Astropy Python library.

PubChem Database Integration

Accesses the PubChem database to query over 110 million chemical compounds, retrieve molecular properties, and perform advanced structural searches.

AlphaFold Database Access

Retrieve and analyze over 200 million AI-predicted protein structures from the AlphaFold DB for structural biology and drug discovery.

PDF Document Toolkit

Manipulates PDF documents programmatically to extract data, create reports, and automate document workflows.

Matchms Mass Spectrometry Analysis

Processes and analyzes mass spectrometry data through spectral similarity, metadata harmonization, and automated workflows.

PyTorch Geometric (PyG) Expert

Builds and trains sophisticated Graph Neural Networks (GNNs) using the PyTorch Geometric library for irregular data structures.

RDKit Cheminformatics

Provides specialized guidance for molecular analysis, structural manipulation, and chemical property calculation using the RDKit library.

Cosmic Cancer Database Integration

Accesses and manages somatic mutation data from the COSMIC database for cancer research and precision oncology.

DeepChem Molecular ML

Streamlines molecular machine learning and drug discovery by providing specialized featurizers, graph neural networks, and chemical benchmark datasets.