Glycoinformatics-assisted Analysis/Prediction Service
Dive Deep into Glycan with Precision and Comprehensiveness
Glycoconjugates play vital roles in many physiological and pathological processes such as intercellular communication, immunity, inflammation, and major diseases. Analyzing and predicting their structures helps research in glycobiology, immunology, etc. CD BioGlyco provides a glycoinformatics-assisted analysis/prediction service by combining multiple assay technologies and bioinformatics tools. We have a team of experienced bioinformatics experts to develop appropriate analysis and prediction programs based on the client's research objectives.
We have extensive experience in the fields of glycoconjugate structure detection, database mining, bioinformatics analysis, etc., and are proficient in the characteristics of various analytical tools. Combining advanced testing techniques, tools, software, and databases, our analysis and prediction consists of the following two parts:
- Detection of structure: Various techniques including high-performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR), mass spectrometry, etc., are used to determine glycan composition, glycosidic bonding, chain branching, sequence, and more.
- Analysis and prediction: We integrate the use of multiple computational methods to visualize the data and help understand and predict glycoconjugates structure, biosynthesis, assembly, function, interactions, and more.
Based on a variety of analytical needs, our service includes, but is not limited to, the following:
We offer customized structure modeling solutions for glycoproteins, proteoglycans, etc., to meet specific client needs. Detection of structures and structural bioinformatics analysis are all accomplished. We aim to understand the spatial structure patterns and interactions of various glycoconjugates by linking multiple data through an efficient workflow.
This service involves visualizing a wide range of data such as NMR, HPLC, electrophoresis, mass spectrometry, and more. We help gain meaningful insights through our interpretation, integration, and visualization.
We identify potential glycosylation sites in protein sequences, including GPI anchor sites, GlcNAcylation sites, etc., through sequence pattern matching, machine learning algorithms, and structure prediction. In addition, we help predict glycan structures based on NMR, infrared spectroscopy (IR), etc., and protein and antibody epitopes.
Our extensive expertise and experience ensure that we perform accurate and reliable statistical analyses of glycosylation sites based on sequence, structure, and surrounding amino acids to understand the structural basis of glycoprotein processing and maturation.
Publication Data
Technology: Machine learning method
Journal: PeerJ Computer Science
IF: 3.8
Published: 2022
Results: This study analyzes and summarizes advances in the discovery of N-linked glycosylation sites using machine learning methods and compares the performance of various tools currently available for predicting such sites. From this paper, we learned some important metrics for feature set construction methods, machine training algorithms, and performance evaluation that provide methodological support for accurate prediction of N-linked glycosylation sites.
Fig.1 Classification of methods for predicting N-linked glycosylation sites. (Akmal, et al., 2022)
Frequently Asked Questions
- How does glycan structure analysis contribute to immunological studies?
Glycans are involved in immune cell recognition processes such as immune cell adhesion and signaling. Glycan structure analysis helps to understand the process of immune cell recognition, identify specific glycan structures associated with different immune cell populations, and explore the functional role of glycans in immune responses.
- How does glycan structure analysis contribute to glycan biomarker development?
Glycan structure analysis is used to identify disease-specific glycan biomarkers. By analyzing and comparing the glycan structure of biomolecules such as control and disease group glycoproteins, researchers identify specific glycans that are altered in certain diseases. These specific glycan biomarkers are used as indicators for early diagnosis of disease.
Applications
- Drug development: Glycoconjugate structure analysis and prediction help to study intermolecular interactions, which is of great value in the drug development process.
- Microbiology research: Glycoconjugate structure analysis and prediction is used to understand the glycan structure of pathogens and to study host-pathogen interactions.
- Glycosylation abnormalities research: Glycosylation abnormalities are associated with a variety of diseases. Glycoconjugate structure analysis and prediction are used to investigate the pathogenesis of diseases.
Our Highlights
- One-stop analysis service: We provide a comprehensive analysis and prediction service, including glycosylation site prediction, diversity of bacterial glycan chain termination chemistry, glycoconjugate structure modeling, etc.
- Comprehensive approach: We analyze large and complex glycobiological data based on various computational tools, software, web, and analytical techniques such as HPLC and NMR.
- Customized solutions: We customize analysis solutions and adjust analysis methods according to clients' needs.
CD BioGlyco provides reliable glycoinformatics-assisted analysis and prediction services based on extensive experience in structure detection and bioinformatics analysis. We look forward to working with you to uncover the mysteries of glycans. Please feel free to contact us for more information if you are interested in this area or have a need.
Reference
- Akmal, M.A.; et al. An analytical study on the identification of N-linked glycosylation sites using a machine learning model. PeerJ Computer Science. 2022, 8: e1069.
For research use only. Not intended for any diagnostic use.
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