Prediction of the Protein O-glycosylation site by Neural Networks and Support Vector Machine

通过神经网络和支持向量机预测蛋白质O-糖基化位点

• 批准号: 19300080
• 负责人: NISHIKAWA Ikuko
• 金额: $ 12.31万
• 依托单位: Ritsumeikan University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2007
• 资助国家: 日本
• 起止时间: 2007 至 2009
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-19300080/
• 关键词: サポート; ベクタ; マシン; O型糖鎖修飾; 機械学習; 哺乳類タンパク質; 天然変性領域; 膜貫通タンパク質; ニューラルネットワーク; 群発と散発; サポート・ベクター・マシン; 独立成分分析; 糖鎖修飾; サポートベクタマシン; 群発的修飾; モチーフ; 進化的保存; 天然変性タンパク質; 半教師あり学習; アミノ酸配列; 立体構造; 二次構造; データベース

O-Glycosylation sites in the mammalian protein is predicted by the machine learning to elucidate the glycosylation mechanisms. Especially, the crowded and the isolated glycosylation sites are separately considered, and it is found that the former is affected by the amino acid composition of the neighboring sites while the latter is affected by the amino acid sequence, and more detailed characteristics are investigated. O-Glycosylation sites are often found in the intrinsically disordered proteins, which lead to the biological understandings of the conservation property, the role in the structural stability and so on. Biological experiments are also executed for a verification of the prediction.

哺乳动物蛋白中的O-糖基化位点可以通过机器学习来阐明糖基化机制。特别是，分别考虑了拥挤的糖基化位点和分离的糖基化位点，发现前者受到相邻部位的氨基酸组成的影响，而后者则受氨基酸序列的影响，并研究了更详细的特征。 O-糖基化位点通常在固有无序的蛋白质中发现，从而导致对保护特性的生物学理解，在结构稳定性中的作用等。还执行生物实验以验证预测。

项目成果

Generalized N-Dimensional Principal Component Analysis (GND-PCA) Based Statistical Appearance Modeling of Facial Images with Multiple Modes

• DOI: 10.2197/ipsjtcva.1.231
• 发表时间: 2009
• 期刊: IPSJ Trans. Comput. Vis. Appl.
• 作者: Xu Qiao;R. Xu;Yenwei Chen;T. Igarashi;K. Nakao;A. Kashimoto

Prediction of the O-Glycosylation by Support Vector Machines and Semi-supervised Learning

• DOI: 10.1007/978-3-642-02490-0_120
• 发表时间: 2008-11
• 作者: Hirotaka Sakamoto;Y. Nakajima;K. Sakakibara;M. Ito;I. Nishikawa

A novel method for gaze tracking by local pattern model and support vector regressor

• DOI: 10.1016/j.sigpro.2009.10.014
• 发表时间: 2010-04-01
• 期刊: SIGNAL PROCESSING
• 影响因子: 4.4
• 作者: Lu, Hu-Chuan;Fang, Guo-Liang;Chen, Yen-Wei
• 通讯作者: Chen, Yen-Wei

PCA based Statistical Shape Model of the Spleen

基于 PCA 的脾脏统计形状模型

• 发表时间: 2009
• 作者: Tomoko Tateyama;Amir H.Foruzan;Yen-Wei Chen
• 通讯作者: Yen-Wei Chen

O-型糖鎖修飾部位の予測における立体構造や生化学的情報の有効性

3D 结构和生化信息在预测 O-糖基化位点中的有效性

• 发表时间: 2008
• 作者: 坂本浩隆;中島有紀子;能野育恵;榊原一紀;伊藤将弘;西川郁子
• 通讯作者: 西川郁子