# Applications of large‐scale artificial intelligence models in bioinformatics

## TL;DR

This paper reviews how large-scale AI models are being used in bioinformatics to analyze complex biological data and improve accuracy.

## Contribution

The paper introduces a classification of large-scale AI models and summarizes their methods, applications, and resources in bioinformatics.

## Key findings

- Large-scale AI models can effectively mine patterns from massive biological datasets.
- The paper categorizes these models into three types and reviews their uses in bioinformatics.
- Challenges and future research directions for AI in bioinformatics are discussed.

## Abstract

Large‐scale artificial intelligence (AI) models can mine potential patterns from massive amounts of data and provide more accurate analyses. This capability has enabled its gradual application in various areas of bioinformatics. However, few reviews have comprehensively summarized the applications of different types of large‐scale AI models in key areas of bioinformatics. Therefore, we first introduce the concept of large‐scale AI models and classify them into three types. Second, we summarize the key methods, applications, and resources of these three types of bioinformatics models. Finally, we discuss challenges and directions for future research. This review provides researchers with a comprehensive perspective to better understand the applications of large‐scale AI models in bioinformatics.