AIMC Topic: Proteome
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SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.
Frontiers in cellular and infection microbiology
Feb 11, 2025
INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge...
Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes.
Molecular & cellular proteomics : MCP
Feb 5, 2025
Citrullination is a critical yet understudied post-translational modification (PTM) implicated in various biological processes. Exploring its role in health and disease requires a comprehensive understanding of the prevalence of this PTM at a proteom...
An AI-assisted morphoproteomic approach is a supportive tool in esophagitis-related precision medicine.
EMBO molecular medicine
Feb 3, 2025
Esophagitis is a frequent, but at the molecular level poorly characterized condition with diverse underlying etiologies and treatments. Correct diagnosis can be challenging due to partially overlapping histological features. By proteomic profiling of...
MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling.
Acta pharmacologica Sinica
Jan 27, 2025
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantial...
PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification.
Journal of proteome research
Jan 22, 2025
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, d...
Deep learning methods for proteome-scale interaction prediction.
Current opinion in structural biology
Jan 22, 2025
Proteome-scale interaction prediction is essential for understanding protein functions and disease mechanisms. Traditional experimental methods are often limited by scale and complexity, driving the need for computational approaches. Deep learning ha...
Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.
Frontiers in cellular and infection microbiology
Jan 13, 2025
INTRODUCTION: This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis.
Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.
Aging cell
Dec 25, 2024
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...
Improved enzyme functional annotation prediction using contrastive learning with structural inference.
Communications biology
Dec 23, 2024
Recent years have witnessed the remarkable progress of deep learning within the realm of scientific disciplines, yielding a wealth of promising outcomes. A prominent challenge within this domain has been the task of predicting enzyme function, a comp...
Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.
International journal of molecular sciences
Dec 21, 2024
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus family with high infectivity and pathogenicity and is the primary pathogen causing the global pandemic of coronavirus disease 2019 (COVID-19). Phosphory...
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