Extracting homologous series from mass spectrometry data by projection on predefined vectors
作者: Johan E. CarlsonJames R. GassonTanja BarthIngvar Eide
作者单位: 1Department of Chemistry, University of Bergen, Allégaten 41, NO-5007 Bergen, Norway
2Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, SE-971 87 Luleå, Sweden
3Statoil Research Centre, NO-7005 Trondheim, Norway
刊名: Chemometrics and Intelligent Laboratory Systems, 2012, Vol.114 , pp.36-43
来源数据库: Elsevier Journal
DOI: 10.1016/j.chemolab.2012.02.007
关键词: ChemometricsCompound classesMass spectrometryFingerprintPrincipal componentsBio oil
原始语种摘要: Abstract(#br)Multivariate statistical methods, such as Principal Component Analysis (PCA), have been used extensively over the past decades as tools for extracting significant information from complex data sets. As such they are very powerful and in combination with an understanding of underlying chemical principles, they have enabled researchers to develop useful models. A drawback with the methods is that they do not have the ability to incorporate any physical / chemical model of the system being studied during the statistical analysis. In this paper we present a method that can be used as a complement to traditional chemometric tools in finding patterns in mass spectrometry data. The method uses a pre-defined set of equally spaced sequences that are assumed to be present in the data....
全文获取路径: Elsevier  (合作)

  • projection 投射
  • spectrometry 光谱测定
  • predefined 预定义
  • series 
  • homologous 同结构型的
  • drawback 回火
  • extracting 选取
  • tools 工具
  • projected 计划中的
  • PCA Primary Communication Attachment