title: Automated procedure for candidate compound selection in GC-MS metabolomics based on prediction of Kovats retention index.
abstract: BACKGROUND
  Matching both the retention index (RI) and the mass spectrum of an unknown compound against a mass spectral reference library provides strong evidence for a correct identification of that compound. Data on retention indices are, however, available for only a small fraction of the compounds in such libraries. We propose a quantitative structure-RI model that enables the ranking and filtering of putative identifications of compounds for which the predicted RI falls outside a predefined window.
  
  
  RESULTS
  We constructed multiple linear regression and support vector regression (SVR) models using a set of descriptors obtained with a genetic algorithm as variable selection method. The SVR model is a significant improvement over previous models built for structurally diverse compounds as it covers a large range (360-4100) of RI values and gives better prediction of isomer compounds. The hit list reduction varied from 41% to 60% and depended on the size of the original hit list. Large hit lists were reduced to a greater extend compared with small hit lists.
  
  
  BACKGROUND
  http://appliedbioinformatics.wur.nl/GC-MS.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.
authors.forename: V V
authors.initials: VV
authors.lastname: Mihaleva
authors.forename: H A
authors.initials: HA
authors.lastname: Verhoeven
authors.forename: R C H
authors.initials: RC
authors.lastname: de Vos
authors.forename: R D
authors.initials: RD
authors.lastname: Hall
authors.forename: R C H J
authors.initials: RC
authors.lastname: van Ham
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D016014:Linear Models; D055432:Metabolomics / Q000379:methods*