title: Algorithms for alignment of mass spectrometry proteomic data.
abstract: BACKGROUND
  The analysis of biological samples with high-throughput mass spectrometers has increased greatly in recent years. As larger datasets are processed, it is important that the spectra are aligned to ensure that the same protein intensities are correctly identified in each sample. Without such an alignment procedure it is possible to make errors in identifying the signals from peptides with similar molecular weight. Two algorithms are provided that can improve the alignment among samples. One algorithm is designed to work with SELDI data produced from a Ciphergen instrument, and the other can be used with data in a more general format.
  
  
  RESULTS
  The two algorithms were applied to samples drawn from a common pool of reference serum. The results indicate substantial improvement in consistently identifying peptide signals in different samples.
authors.affiliation: National Institute of Neurological Disorders and Stroke, National Institutes of Health Bethesda, MD 20892, USA. neal.jeffries@nih.gov
authors.forename: Neal
authors.initials: N
authors.lastname: Jeffries
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D008969:Molecular Sequence Data; D010449:Peptide Mapping / Q000379:methods*; D020543:Proteome / Q000032:analysis* / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
chemical_list: D020543:Proteome