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 …
[HTML][HTML] Informatic challenges and advances in illuminating the druggable proteome
Highlights•Prediction of understudied protein kinase and pseudokinase functions using
evolutionary inference.•Integration and mining of heterogeneous data sources for drug …
evolutionary inference.•Integration and mining of heterogeneous data sources for drug …
Evaluating representation learning on the protein structure universe
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation
learning on protein structures with Geometric Graph Neural Networks. We consider large …
learning on protein structures with Geometric Graph Neural Networks. We consider large …
DeepKlapred: A deep learning framework for identifying protein lysine lactylation sites via multi-view feature fusion
Lysine lactylation (Kla) is a post-translational modification (PTM) that holds significant
importance in the regulation of various biological processes. While traditional experimental …
importance in the regulation of various biological processes. While traditional experimental …
Immunopeptidomics for autoimmunity: unlocking the chamber of immune secrets
T cells mediate pathogenesis of several autoimmune disorders by recognizing self-epitopes
presented on Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) …
presented on Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) …
MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm
Protein phosphorylation is essential in various signal transduction and cellular processes.
To date, most tools are designed for model organisms, but only a handful of methods are …
To date, most tools are designed for model organisms, but only a handful of methods are …
Current computational tools for protein lysine acylation site prediction
Z Qin, H Ren, P Zhao, K Wang, H Liu… - Briefings in …, 2024 - academic.oup.com
As a main subtype of post-translational modification (PTM), protein lysine acylations (PLAs)
play crucial roles in regulating diverse functions of proteins. With recent advancements in …
play crucial roles in regulating diverse functions of proteins. With recent advancements in …
Sitetack: a deep learning model that improves PTM prediction by using known PTMs
CS Gutierrez, AA Kassim, BD Gutierrez… - …, 2024 - academic.oup.com
Abstract Motivation Post-translational modifications (PTMs) increase the diversity of the
proteome and are vital to organismal life and therapeutic strategies. Deep learning has been …
proteome and are vital to organismal life and therapeutic strategies. Deep learning has been …
Substrate prediction for RiPP biosynthetic enzymes via masked language modeling and transfer learning
Ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthetic
enzymes often exhibit promiscuous substrate preferences that cannot be reduced to simple …
enzymes often exhibit promiscuous substrate preferences that cannot be reduced to simple …
Post‐translational modifications of proteins in cardiovascular diseases examined by proteomic approaches
M Stastna - The FEBS Journal, 2024 - Wiley Online Library
Over 400 different types of post‐translational modifications (PTMs) have been reported and
over 200 various types of PTMs have been discovered using mass spectrometry (MS) …
over 200 various types of PTMs have been discovered using mass spectrometry (MS) …