AIMC Topic: Glycomics
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Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma.
Journal of proteome research
Apr 21, 2025
The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal...
GNOme, an ontology for glycan naming and subsumption.
Analytical and bioanalytical chemistry
Feb 8, 2025
While GlyTouCan provides stable identifiers for referencing glycan structures, they are not organized semantically. GNOme, a glycan naming and subsumption ontology and a member of the OBOFoundry, organizes GlyTouCan accessions for automated reasoning...
Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.
Computers in biology and medicine
Jan 27, 2025
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three l...
Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition.
International journal of molecular sciences
Sep 16, 2024
In immunoglobulin G (IgG), -glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates...
Navigating the maze of mass spectra: a machine-learning guide to identifying diagnostic ions in O-glycan analysis.
Analytical and bioanalytical chemistry
Aug 24, 2024
Structural details of oligosaccharides, or glycans, often carry biological relevance, which is why they are typically elucidated using tandem mass spectrometry. Common approaches to distinguish isomers rely on diagnostic glycan fragments for annotati...
Predicting glycan structure from tandem mass spectrometry via deep learning.
Nature methods
Jul 1, 2024
Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throug...
Glycoinformatics in the Artificial Intelligence Era.
Chemical reviews
Aug 12, 2022
Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and t...
Artificial intelligence in the analysis of glycosylation data.
Biotechnology advances
Jun 20, 2022
Glycans are complex, yet ubiquitous across biological systems. They are involved in diverse essential organismal functions. Aberrant glycosylation may lead to disease development, such as cancer, autoimmune diseases, and inflammatory diseases. Glycan...
Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed.
Clinica chimica acta; international journal of clinical chemistry
Feb 25, 2018
In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay ...
Automated, high-throughput serum glycoprofiling platform.
Integrative biology : quantitative biosciences from nano to macro
Jul 20, 2015
Complex carbohydrates are rapidly becoming excellent biomarker candidates because of their high sensitivity to pathological changes. However, the discovery of clinical glycobiomarkers has been slow, due to the scarcity of high-throughput glycoanalyti...
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