Glycan Electrophoresis Data Interpretation, Integration and Visualization
Integrate Glycan Electrophoresis Data Systems and Formats
Combining glycomics and computational engineering, CD BioGlyco provides a high-precision Glycoinformatics-assisted Analysis/Prediction Service. Electrophoresis is a glycan analysis technique with high resolution, high sensitivity, and high-throughput performance. Our team with superb algorithms helps clients all over the world to Visualize Glycan Data efficiently.
Automated identification and quantitation
Based on Gaussian approximations, CD BioGlyco provides high-quality electrophoresis data processing solutions for accurate glycan assignments and quantitation. Combining semi-automated and manual assignments, our researchers quantify large volumes of electrophoresis data after classification.
Peak detection and quantitation
The effects of temperature, sample complexity, pH, and other physicochemical fluctuations during analysis cause drift in peak migration and area under the curve. CD BioGlyco uses Riemann approximation to provide peak detection and quantitation of non-Gaussian peaks.
Relying on fast algorithms, we offer parameter-specific control and trimming services to help customers adjust for misaligned data. Our lab offers a checking service for automatically selected peaks and tuning parameters by high-throughput calculations.
Data visualization
Our computational team uses a clustering algorithm to classify large cohort electrophoresis datasets. Moreover, we provide Gaussian model comparison and alignment services for both large cohort data and electrophoresis data.
Our researchers use unsupervised clustering and peak intensity as input variables to group electrophoretic plots. Visual presentation of electropherograms by covering each cluster helps clients to generate usable data plots directly.
Publication
Technology: Cell culture, Capillary electrophoresis-laser-induced fluorescence (CE-LIF)
Journal: Beilstein Journal of Organic Chemistry
Published: 2020
IF: 2.2
Results: Researchers have developed a new strategy for the interpretation, integration, and visualization of large cohorts of CE-LIF electropherograms, which are split into smaller, more manageable groups of similar electropherograms and then manually defined using open-source software to define their peak areas. This strategy combines the advantages of automated calculations and manual assignments to run efficiently in glycan identification and quantitative analysis. Using this strategy, researchers have demonstrated its effectiveness by comprehensively characterizing the glycosylation profiles of anti-HER2 antibody products.
Fig.1 Plots clustering and calibration into three clusters of similar electropherograms. (Walsh, et al., 2020)
Applications
- Glycan electrophoresis data visualization is well suited for assessing glycan similarity in biological samples.
- Glycan electrophoresis data visualization can be used for large cohort glycomics data analysis.
- Glycan electrophoresis data visualization can be used for batch glycosylation analysis in biopharmaceutical development.
Advantages of Us
- Our researchers quickly select peaks before quantification by clustering and migration time calibration to handle large amounts of electrophoretic data.
- The tools we provide outperform traditional algorithms in terms of processing time and alignment accuracy for high-resolution datasets.
- Our tool supports simultaneous analysis of large queues (thousands of runs) of data.
Frequently Asked Questions
- What types of electrophoresis data can be processed?
- Our computational team supports the processing of electrophoresis data from a variety of types and sources including but not limited to CE-LIF, agarose gel electrophoresis, polyacrylamide gel electrophoresis, starch gel electrophoresis, cellulose acetate electrophoresis, glass powder electrophoresis, and more!
- Is there any leakage of raw data when using analytics tools?
- Our company takes extra care to protect the privacy and integrity of our client's data. Our analytical tools have strong security measures such as version control, data locking, and code control to protect the analytical tools and analyzed data.
CD BioGlyco uses advanced algorithmic systems and a reliable analytical team to provide electrophoresis data processing services for our clients. Our goal is to complete every glycan data visualization task quickly and efficiently. Please feel free to contact us.
Reference
- Walsh, I.; et al. Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations. Beilstein Journal of Organic Chemistry. 2020, 16(1): 2087-2099.
For research use only. Not intended for any diagnostic use.
Related Services
