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Applications of large-scale artificial intelligence models in bioinformatics.

Mingjing Li1, Qichen Shang1, Ziyang Dong1

  • 1College of Computer Science Sichuan University Chengdu China.

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Summary

Large-scale artificial intelligence (AI) models offer advanced data analysis in bioinformatics. This review categorizes AI models, detailing their bioinformatics applications, methods, and future research directions.

Keywords:
artificial intelligencebioinformaticslarge‐scale language modelslarge‐scale multimodal modelslarge‐scale vision models

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Area of Science:

  • Bioinformatics
  • Artificial Intelligence

Background:

  • Large-scale artificial intelligence (AI) models excel at identifying patterns in extensive datasets, leading to enhanced analytical accuracy.
  • The application of AI in bioinformatics is growing, yet comprehensive reviews on different AI model types are scarce.

Purpose of the Study:

  • To introduce and classify large-scale AI models into three distinct types.
  • To summarize the methods, applications, and resources associated with these AI models in bioinformatics.
  • To discuss current challenges and future research avenues in the field.

Main Methods:

  • Conceptual introduction and classification of large-scale AI models.
  • Systematic review of AI model applications, methodologies, and available resources in bioinformatics.
  • Analysis of challenges and future research directions.

Main Results:

  • Categorization of large-scale AI models into three primary types.
  • Detailed overview of the methods and applications of each AI model type within bioinformatics.
  • Identification of key resources and tools for utilizing these models.

Conclusions:

  • Large-scale AI models are increasingly vital in bioinformatics for advanced data analysis.
  • This review offers a comprehensive perspective on AI applications, aiding researchers in understanding and utilizing these powerful tools.