Leveraging transformers‐based language models in proteome bioinformatics
NQK Le - Proteomics, 2023 - Wiley Online Library
In recent years, the rapid growth of biological data has increased interest in using
bioinformatics to analyze and interpret this data. Proteomics, which studies the structure …
bioinformatics to analyze and interpret this data. Proteomics, which studies the structure …
BioLiP2: an updated structure database for biologically relevant ligand–protein interactions
C Zhang, X Zhang, PL Freddolino… - Nucleic Acids …, 2024 - academic.oup.com
With the progress of structural biology, the Protein Data Bank (PDB) has witnessed rapid
accumulation of experimentally solved protein structures. Since many structures are …
accumulation of experimentally solved protein structures. Since many structures are …
Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion
Protein function prediction is an essential task in bioinformatics which benefits disease
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model
Motivation Identifying the B-cell epitopes is an essential step for guiding rational vaccine
development and immunotherapies. Since experimental approaches are expensive and …
development and immunotherapies. Since experimental approaches are expensive and …
A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond
Proteins interact with diverse ligands to perform a large number of biological functions, such
as gene expression and signal transduction. Accurate identification of these protein–ligand …
as gene expression and signal transduction. Accurate identification of these protein–ligand …
Fast and accurate protein intrinsic disorder prediction by using a pretrained language model
Determining intrinsically disordered regions of proteins is essential for elucidating protein
biological functions and the mechanisms of their associated diseases. As the gap between …
biological functions and the mechanisms of their associated diseases. As the gap between …
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Revealing protein binding sites with other molecules, such as nucleic acids, peptides, or
small ligands, sheds light on disease mechanism elucidation and novel drug design. With …
small ligands, sheds light on disease mechanism elucidation and novel drug design. With …
Accurately identifying nucleic-acid-binding sites through geometric graph learning on language model predicted structures
The interactions between nucleic acids and proteins are important in diverse biological
processes. The high-quality prediction of nucleic-acid-binding sites continues to pose a …
processes. The high-quality prediction of nucleic-acid-binding sites continues to pose a …
MucLiPred: Multi-Level Contrastive Learning for Predicting Nucleic Acid Binding Residues of Proteins
Protein–molecule interactions play a crucial role in various biological functions, with their
accurate prediction being pivotal for drug discovery and design processes. Traditional …
accurate prediction being pivotal for drug discovery and design processes. Traditional …
GPSFun: geometry-aware protein sequence function predictions with language models
Q Yuan, C Tian, Y Song, P Ou, M Zhu… - Nucleic Acids …, 2024 - academic.oup.com
Abstract Knowledge of protein function is essential for elucidating disease mechanisms and
discovering new drug targets. However, there is a widening gap between the exponential …
discovering new drug targets. However, there is a widening gap between the exponential …