Awesome AI for Immunology

A curated collection of AI resources for immunologists and virologists, featuring high-throughput methods, computational tools, and practical guides to accelerate research, discovery, and translational applications.

This repository is designed to help experimentalists effectively harness the power of AI for their work — from analyzing complex datasets to predicting immune responses.

Overview

84
AI Papers
71
High-Throughput Studies
15+
Categories
100%
Open Source

Key Features

  • High-throughput screening methods and datasets
  • Comprehensive collection of AI tools for immunology research
  • Interactive tables with search and filtering capabilities
  • Direct links to papers, repositories, and tools
  • Regular updates with latest research

High-Throughput Methods

Explore cutting-edge high-throughput screening methods and experimental techniques used in immunology research.

High-Throughput Screening Studies

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AI Tools

Discover powerful AI tools, models, and computational methods specifically designed for immunology and virology research.

AI in Immunology Papers

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AI Modeling Guide

Interactive guide to help you choose the right AI approach for your immunology research. Answer a few questions to get personalized recommendations.

What type of data are you working with?

What is your research goal?

How much data do you have?

Recommended AI Approach

Quick Reference

Sequence Analysis

  • Small data: Random Forest, SVM
  • Medium data: CNN, LSTM
  • Large data: Transformer, BERT

Structure Analysis

  • Small data: Traditional ML
  • Medium data: Graph Neural Networks
  • Large data: AlphaFold, ESMFold

Expression Analysis

  • Small data: Linear models
  • Medium data: scVI, scanpy
  • Large data: scGPT, CellBERT

Image Analysis

  • Small data: Transfer learning
  • Medium data: ResNet, VGG
  • Large data: Vision Transformer

Contributing

Contributions are welcome! Help us build the most comprehensive collection of AI resources for immunology.

Please feel free to submit a pull request with additional resources, or open an issue if you'd like to suggest improvements.

Contribute on GitHub