A Feature Grouping Technique Based on Biclustering for the Analysis of LC-MS Metabolomic Data

• 作 者: XiaohuiLin[1]RuiZhang[1]LinaZhou[2]PeiyuanYin[2]GuowangXu[2]
• 机 构: School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
• 出 处: 第2届大连国际色谱学术报告会、第37届国际高效液相色谱及相关技术会议、第18届全国色谱学术报告会
• 发表日期: 2011年期

　　Metabolomics has shown a promising application in many fields such as disease diagnosis, drug development.Liquid chromatography-mass spectrometry (LC-MS) is one of its main analysis techniques.HPLC-MS metabolomic data is usually of high dimension.Among the large features, some are related to each other and contain the similar information about the problem.Grouping the features correctly is very meaningful for getting a comprehension of the problem studied and building a more efficient classification model.