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Updated: May 26, 2025
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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
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Foundation models of protein sequences: A brief overview
Andreas Bjerregaard1, Peter Mørch Groth2, Søren Hauberg3
1Department of Computer Science, University of Copenhagen, Copenhagen, Denmark; Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark.
Current Opinion in Structural Biology
|February 21, 2025
Summary
Protein sequence models have advanced to foundation models using self-supervised learning and large datasets. These models are crucial for protein science, enabling better representations, design, and fine-tuning.
Area of Science:
- Computational biology
- Bioinformatics
- Structural biology
Background:
- Protein sequence models have evolved significantly from basic statistical methods to sophisticated foundation models.
- Self-supervised learning and vast amounts of protein sequence data have driven this evolution.
- Foundation models are now integral to protein science, offering enhanced capabilities.
Purpose of the Study:
- To review the historical development of protein sequence models.
- To categorize recent trends in protein modeling methodologies.
- To outline future perspectives in the field.
Main Methods:
- Tracing the evolution of protein sequence modeling techniques.
- Categorizing models based on data modalities and conditioning contexts.
- Analyzing recent advancements and emerging trends.
Main Results:
- Foundation models represent a major leap in protein sequence modeling capabilities.
- These models facilitate improved protein representations and generative design.
- Recent trends focus on diverse modalities and conditioning contexts.
Conclusions:
- Protein sequence foundation models are transforming protein science.
- Continued advancements promise further innovation in protein design and analysis.
- The review highlights key trends and future research directions.
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