GlycoExtractor: A Web-Based Interface for High Throughput Processing of HPLC-Glycan Data

被引：17

作者：

Artemenko, Natalia V. ^{[1
]}

Campbell, Matthew P. ^{[1
]}

Rudd, Pauline M. ^{[1
]}

机构：

[1] Natl Univ Ireland Univ Coll Dublin, Dublin Oxford Glycobiol Lab, NIBRT, Conway Inst, Dublin 4, Ireland

来源：

JOURNAL OF PROTEOME RESEARCH | 2010年 / 9卷 / 04期

关键词：

glycomics data analysis; data extraction; glycome informatics; glycan database; xml format in glycomics; web-based extractor; standards; HPLC; carbohydrates; high-throughput; SERUM GLYCOPROTEINS; MINIMUM INFORMATION; MASS-SPECTROMETRY; OVARIAN-CANCER; GLYCOSYLATION; PROTEOMICS; GLYCOMICS; REPRESENTATION; GLYCOBIOLOGY; STANDARDS;

D O I：

10.1021/pr901213u

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Recently, an automated high-throughput HPLC platform has been developed that can be used to fully sequence and quantify low concentrations of N-linked sugars released from glycoproteins, supported by an experimental database (GlycoBase) and analytical tools (autoGU). However, commercial packages that support the operation of HPLC instruments and data storage lack platforms for the extraction of large volumes of data. The lack of resources and agreed formats in glycomics is now a major limiting factor that restricts the development of bioinformatic tools and automated workflows for high-throughput HPLC data analysis. GlycoExtractor is a web-based tool that interfaces with a commercial HPLC database/software solution to facilitate the extraction of large volumes of processed glycan profile data (peak number, peak areas, and glucose unit values). The tool allows the user to export a series of sample sets to a set of file formats (XML, JSON, and CSV) rather than a collection of disconnected files. This approach not only reduces the amount of manual refinement required to export data into a suitable format for data analysis but also opens the field to new approaches for high-throughput data interpretation and storage, including biomarker discovery and validation and monitoring of online bioprocessing conditions for next generation biotherapeutics.

引用

页码：2037 / 2041

页数：5

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