Advancing plant biology through deep learning-powered natural language processing
S Peng, L Rajjou - Plant Cell Reports, 2024 - Springer
The application of deep learning methods, specifically the utilization of Large Language
Models (LLMs), in the field of plant biology holds significant promise for generating novel …
Models (LLMs), in the field of plant biology holds significant promise for generating novel …
Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach
This study introduces an innovative strategy for the rapid and accurate identification of
pesticide residues in agricultural products by combining surface-enhanced Raman …
pesticide residues in agricultural products by combining surface-enhanced Raman …
Enhancing antibody language models with structural information
The central tenet of molecular biology is that a protein's amino acid sequence determines its
three-dimensional structure, and thus its function. However, proteins with similar sequences …
three-dimensional structure, and thus its function. However, proteins with similar sequences …
Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering
P Cheng, C Mao, J Tang, S Yang, Y Cheng, W Wang… - Cell Research, 2024 - nature.com
Mutations in amino acid sequences can provoke changes in protein function. Accurate and
unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but …
unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but …
Pepharmony: A multi-view contrastive learning framework for integrated sequence and structure-based peptide encoding
Recent advances in protein language models have catalyzed significant progress in peptide
sequence representation. Despite extensive exploration in this field, pre-trained models …
sequence representation. Despite extensive exploration in this field, pre-trained models …
[PDF][PDF] Jointly Embedding Protein Structures and Sequences through Residue Level Alignment
The relationships between protein sequences, structures, and their functions are determined
by complex codes that scientists aim to decipher. While structures contain key information …
by complex codes that scientists aim to decipher. While structures contain key information …
Large protein databases reveal structural complementarity and functional locality
P Szczerbiak, L Szydlowski, W Wydmanski… - bioRxiv, 2024 - biorxiv.org
Recent breakthroughs in protein structure prediction have led to an unprecedented surge in
high-quality 3D models, highlighting the need for efficient computational solutions to …
high-quality 3D models, highlighting the need for efficient computational solutions to …
Prot2Token: A multi-task framework for protein language processing using autoregressive language modeling
This paper proposes a versatile tokenization method and introduces Prot2Token, a model
that combines autoregressive language modeling with protein language models (PLMs) to …
that combines autoregressive language modeling with protein language models (PLMs) to …