title: Analytical model of peptide mass cluster centres with applications.
abstract: BACKGROUND
  The elemental composition of peptides results in formation of distinct, equidistantly spaced clusters across the mass range. The property of peptide mass clustering is used to calibrate peptide mass lists, to identify and remove non-peptide peaks and for data reduction.
  
  
  RESULTS
  We developed an analytical model of the peptide mass cluster centres. Inputs to the model included, the amino acid frequencies in the sequence database, the average length of the proteins in the database, the cleavage specificity of the proteolytic enzyme used and the cleavage probability. We examined the accuracy of our model by comparing it with the model based on an in silico sequence database digest. To identify the crucial parameters we analysed how the cluster centre location depends on the inputs. The distance to the nearest cluster was used to calibrate mass spectrometric peptide peak-lists and to identify non-peptide peaks.
  
  
  CONCLUSIONS
  The model introduced here enables us to predict the location of the peptide mass cluster centres. It explains how the location of the cluster centres depends on the input parameters. Fast and efficient calibration and filtering of non-peptide peaks is achieved by a distance measure suggested by Wool and Smilansky.
authors.affiliation: School of Mathematics and Statistics, Merz Court, University of Newcastle upon Tyne, NE1 7RU, UK. w.e.wolski@ncl.ac.uk
authors.forename: Witold E
authors.initials: WE
authors.lastname: Wolski
authors.forename: Malcolm
authors.initials: M
authors.lastname: Farrow
authors.forename: Anne-Katrin
authors.initials: AK
authors.lastname: Emde
authors.forename: Hans
authors.initials: H
authors.lastname: Lehrach
authors.forename: Maciej
authors.initials: M
authors.lastname: Lalowski
authors.forename: Knut
authors.initials: K
authors.lastname: Reinert