Data Science & ML Claude 技能

ETE Toolkit for Phylogenetics

Manipulates, analyzes, and visualizes phylogenetic and hierarchical trees for biological research and genomic data.

NCBI GEO Database Explorer

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

Statistical Analysis Toolset

Performs comprehensive hypothesis testing, regression analysis, and Bayesian statistics with automated assumption checking and APA-style reporting.

PyMC Bayesian Modeling

Builds and validates complex Bayesian models using PyMC's probabilistic programming framework.

Torch Tensor Parallelism

Implements distributed tensor parallel operations in PyTorch, focusing on efficient weight sharding and collective operations across multiple GPUs.

Biopython for Bioinformatics

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

ClinPGx Pharmacogenomics Database

Accesses comprehensive pharmacogenomics data including gene-drug interactions, CPIC guidelines, and genotype-guided dosing recommendations.

Largest Eigenvalue Optimization

Optimizes numerical linear algebra computations for finding eigenvalues of small dense matrices through direct LAPACK integration and overhead reduction.

KEGG Database Pathway Analysis

Accesses the KEGG REST API to perform biological pathway analysis, gene-pathway mapping, and metabolic network research.

AlphaFold Database Access

Facilitates the retrieval and analysis of over 200 million AI-predicted protein structures from the AlphaFold DB for biological research and drug discovery.

Transformers

Integrates state-of-the-art machine learning models for NLP, computer vision, and audio tasks using the Hugging Face ecosystem.

Bayesian Network Recovery and Modification

Guides the recovery of Directed Acyclic Graph structures from observational data, parameter estimation, and the implementation of causal interventions.

Data Commons Client

Accesses global statistical data from the Data Commons knowledge graph to analyze demographics, economics, health, and environmental trends.

Scientific Data Visualization

Generates publication-quality scientific figures and multi-panel layouts compliant with major journal standards.

DrugBank Database

Accesses and analyzes comprehensive pharmaceutical data from DrugBank to perform drug discovery research, interaction analysis, and target identification.

PathML

Analyzes whole-slide pathology images and multiparametric imaging data using computational tools for tissue segmentation, spatial graphs, and machine learning.

Exploratory Data Analysis Toolkit

Automates comprehensive statistical analysis and visual profiling for diverse datasets to uncover hidden patterns, anomalies, and actionable insights.

NCBI Gene Database Tools

Queries and retrieves genomic data from NCBI Gene databases using E-utilities and the modern Datasets API.

PyTorch Lightning

Organizes and scales PyTorch deep learning workflows by automating training loops, hardware orchestration, and boilerplate code.

TorchDrug Scientific Computing

Accelerates drug discovery and molecular research by providing specialized tools for graph neural networks, protein modeling, and chemical property prediction.

COBRApy Metabolic Modeling

Facilitates constraint-based reconstruction and analysis (COBRA) of metabolic models for systems biology and metabolic engineering.

Pymoo Optimization

Implements advanced multi-objective and many-objective optimization frameworks using state-of-the-art evolutionary algorithms and Pareto analysis.

PyDESeq2 Gene Expression Analysis

Identifies differentially expressed genes from bulk RNA-seq counts using the PyDESeq2 statistical framework.

Torch Pipeline Parallelism

Implements distributed model training by partitioning PyTorch layers across multiple GPUs using pipeline parallelism patterns like AFAB and 1F1B.

scvi-tools

Empowers single-cell omics analysis with deep generative models for dimensionality reduction, batch correction, and multimodal data integration.

Dask Parallel Computing

Enables parallel and distributed computing in Python to scale pandas and NumPy operations beyond memory limits.

Torch Tensor Parallelism

Implements distributed tensor-parallel linear layers in PyTorch to enable training of models that exceed single-device memory limits.

Polars High-Performance Data Analysis

Optimizes data processing workflows using the high-performance Polars DataFrame library and expression API.

ReLU Network Model Extraction

Extracts hidden layer weight matrices from black-box ReLU neural networks using input-output query patterns and geometric analysis.

Statsmodels Statistical Analysis

Performs rigorous statistical modeling, econometric analysis, and hypothesis testing using Python's statsmodels library.