Data Science & ML Claude 技能

Statistical Analysis

Performs professional statistical modeling, hypothesis testing, and rigorous assumption verification with publication-ready APA reporting.

DiffDock Molecular Docking

Predicts high-accuracy 3D protein-ligand binding poses using state-of-the-art diffusion-based deep learning models.

Scanpy Single-Cell Analysis

Performs comprehensive single-cell RNA-seq analysis workflows including quality control, normalization, clustering, and cell-type annotation.

Seaborn Statistical Visualization

Generates publication-quality statistical graphics and complex data visualizations using the Seaborn Python library.

SHAP Model Interpretability

Explains machine learning model predictions and feature importance using Shapley values for improved transparency and debugging.

Transformers

Implements, fine-tunes, and deploys pre-trained transformer models for natural language processing, computer vision, and audio tasks.

PufferLib RL

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

LaminDB

Manages biological datasets with end-to-end lineage tracking, ontology-based curation, and FAIR data principles using a unified Python API.

Stable Baselines3

Implements reinforcement learning workflows including agent training, custom environment design, and parallelized experimentation using the Stable Baselines3 library.

NeuroKit2

Processes and analyzes physiological signals like ECG, EEG, and EDA to extract research-grade biometrics and psychophysiological insights.

Vaex Data Analysis

Processes and visualizes billion-row tabular datasets exceeding available RAM through lazy, out-of-core DataFrame operations.

SymPy Symbolic Mathematics

Executes exact symbolic mathematics in Python to solve equations, perform calculus, and manipulate algebraic expressions with mathematical precision.

Scikit Survival

Performs advanced survival analysis and time-to-event modeling in Python using specialized machine learning techniques for censored data.

Biomni Biomedical AI

Executes complex autonomous biomedical research tasks across genomics, drug discovery, and clinical analysis using integrated databases and code execution.

OpenAlex Database

Queries and analyzes millions of scholarly works, authors, and institutions using the OpenAlex API to facilitate comprehensive bibliometric research.

Denario Scientific Research

Automates the end-to-end scientific research lifecycle from data-driven hypothesis generation to the production of publication-ready LaTeX manuscripts.

AnnData

Manages and analyzes annotated data matrices for single-cell genomics and large-scale biological datasets in Python.

Exploratory Data Analysis

Conducts automated exploratory data analysis on over 200 scientific file formats to extract metadata, assess quality, and generate comprehensive documentation reports.

Aeon Time Series Machine Learning

Provides specialized algorithms and workflows for comprehensive time series analysis, including classification, forecasting, and anomaly detection.

Cirq Quantum Computing

Designs, simulates, and executes quantum circuits across diverse hardware backends and simulators using Google's open-source framework.

DrugBank Database

Accesses and analyzes comprehensive pharmaceutical data from DrugBank including molecular structures, drug interactions, targets, and pharmacological properties.

SimPy Simulation

Models complex discrete-event systems where entities interact with shared resources over time using process-based Python simulations.

Astropy Astrophysics Toolkit

Facilitates advanced astronomical research and data analysis using Python for coordinate transformations, FITS file manipulation, and cosmological calculations.

Histolab

Processes digital pathology whole slide images (WSI) through automated tissue detection, tile extraction, and specialized image preprocessing.

Scientific Hypothesis Generation

Generates and tests scientific hypotheses from observational data and research literature to accelerate empirical discovery and predictive modeling.

PathML Computational Pathology

Analyzes whole-slide pathology images and multiparametric imaging data using advanced machine learning, spatial graph construction, and automated preprocessing pipelines.

Scientific Resource Detection

Detects system hardware capabilities and generates strategic recommendations for optimized scientific computing and data processing tasks.

Data Commons Client

Provides programmatic access to global statistical data, demographics, and economic indicators via the Data Commons knowledge graph.

PyHealth Healthcare AI

Develops, tests, and deploys healthcare-specific machine learning models using clinical data, medical coding systems, and physiological signals.

scvi-tools Single-Cell Analysis

Analyzes single-cell genomics data using probabilistic deep generative models for tasks like batch correction, cell type annotation, and multi-omic integration.