[HTML][HTML] Teaching AI to speak protein

M Heinzinger, B Rost - Current Opinion in Structural Biology, 2025 - Elsevier
Highlights•Protein Language Models (pLMs) tap into large unlabeled data to transform
protein science.•pLMs boost protein structure and function prediction performance and …

Genomic language models: opportunities and challenges

G Benegas, C Ye, C Albors, JC Li, YS Song - Trends in Genetics, 2025 - cell.com
Large language models (LLMs) are having transformative impacts across a wide range of
scientific fields, particularly in the biomedical sciences. Just as the goal of natural language …

Protrek: Navigating the protein universe through tri-modal contrastive learning

J Su, X Zhou, X Zhang, F Yuan - bioRxiv, 2024 - biorxiv.org
ProTrek redefines protein exploration by seamlessly fusing sequence, structure, and natural
language function (SSF) into an advanced tri-modal language model. Through contrastive …

Gaia: A Context-Aware Sequence Search and Discovery Tool for Microbial Proteins

N Jha, J Kravitz, J West-Roberts, A Camargo, S Roux… - bioRxiv, 2024 - biorxiv.org
Protein sequence similarity search is fundamental to genomics research, but current
methods are typically not able to consider crucial genomic context information that can be …

Limitations and Enhancements in Genomic Language Models: Dynamic Selection Approach

S Qiu - bioRxiv, 2024 - biorxiv.org
Genomic Language Models (GLMs), which learn from nucleotide sequences, have become
essential tools for understanding the principles of life and have demonstrated outstanding …