alexa Development of a data-mining system for differential profiling of cell glycoproteins based on lectin microarray | OMICS International | Abstract
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
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Research Article

Development of a data-mining system for differential profiling of cell glycoproteins based on lectin microarray

Atsushi Kuno1#, Yoko Itakura1#, Masashi Toyoda2, Yoriko Takahashi3, Masao Yamada4, Akihiro Umezawa2, and Jun Hirabayashi1*

1Research Center for Medical Glycoscience (RCMG), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1, Umezono, Tsukuba, Ibaraki 305-8568, Japan

2Department of Reproductive Biology and Pathology, National Research Institute for Child Health and Development, 2-10-1, Okura, Setagaya, Tokyo, 157-8535, Japan

3Bioscience Group, Mitsui Knowledge Industry Co., Ltd., Hitotsubashi SI bldg., 3-26, Kandanishikicho, Chiyoda-ku, Tokyo 101-0054, Japan

4Glycomics Research Laboratory, Moritex Corporation, 1-3-3, Azamino-Minami, Aoba-ku, Yokohama City, Kanagawa 225-0012, Japan

#These authors contributed equally to this study

*Corresponding Author:
Dr. Jun Hirabayashi
Research Center for Medical Glycoscience
National Institute of Advanced
Industrial Science and Technology
AIST Tsukuba Central 2, 1-1-1, Umezono
Tsukuba, Ibaraki 305-8568, Japan
Tel: +81-29-861-3124,
Fax : +81-29-861-3125,
E-mail : [email protected]

Received Date: April 15, 2008; Accepted Date: May 14, 2008; Published Date: May 20, 2008

Citation: Atsushi K, Yoko I, Masashi T, Yoriko T, Masao Y, et al. (2008) Development of a Data-mining System for Differential Profiling of Cell Glycoproteins Based on Lectin Microarray. J Proteomics Bioinform 1: 068-072. doi: 10.4172/jpb.1000011

Copyright: © 2008 Atsushi K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Lectin microarray is an emerging technique enabling multiplex glycan profiling in a direct, rapid and sensitive manner. So far, there has been no robust system available for efficient data-mining to realize differential profiling, which is an effective approach to biomarker investigation. In the present paper, we describe a practical strategy for proteomics-based glycan-related biomarker discovery, with an example of mice embryonal carcinoma and embryonic stem cells and their differentiated forms with retinoic acid. Data were processed by the microarray system using a max-normalization procedure after a gain-merging process, followed by principal component analysis.

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