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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.

Frontiers in cellular and infection microbiology
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.

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

Frontiers in cellular and infection microbiology
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
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
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...

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.

Nature communications
Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address th...

Proteomics and Machine Learning-Based Approach to Decipher Subcellular Proteome of Mouse Heart.

Molecular & cellular proteomics : MCP
Protein compartmentalization to distinctive subcellular niches is critical for cardiac function and homeostasis. Here, we employed a rapid and robust workflow based on differential centrifugal-based fractionation with mass spectrometry-based proteomi...

AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning.

The plant genome
The organization of subcellular components in a cell is critical for its function and studying cellular processes, protein-protein interactions, identifying potential drug targets, network analysis, and other systems biology mechanisms. Determining p...

[Serum proteomics and machine learning unveil new diagnostic biomarkers for tuberculosis in adolescents and young adults].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recr...

Deep learning tools predict variants in disordered regions with lower sensitivity.

BMC genomics
BACKGROUND: The recent AI breakthrough of AlphaFold2 has revolutionized 3D protein structural modeling, proving crucial for protein design and variant effects prediction. However, intrinsically disordered regions-known for their lack of well-defined ...

Uncovering hepatic transcriptomic and circulating proteomic signatures in MASH: A meta-analysis and machine learning-based biomarker discovery.

Computers in biology and medicine
BACKGROUND: Metabolic-associated steatohepatitis (MASH), the progressive form of metabolic-associated steatotic liver disease (MASLD), poses significant risks for liver fibrosis and cardiovascular complications. Despite extensive research, reliable b...