title: Computational aspects of protein identification by mass spectrometry.
abstract: Recent developments in proteomics and genomics provide huge quantities of data to analyze. Automatic interpretation of mass spectrometry data has become essential for high-throughput processes aiming to study complete proteomes. There exist two main sources of mass spectrometric data: peptide mass fingerprint and fragmentation spectra, both of which require specific bioinformatic algorithms. We present a survey of these algorithms and discuss the efficiency of the different approaches and the possible improvements that may lead to a complete automatic high-throughput identification process.
authors.affiliation: Protein Informatics Group, Swiss Institute of Bioinformatics, CMU, Geneva. robin.gras@isb-sib.ch
authors.forename: R
authors.initials: R
authors.lastname: Gras
authors.forename: M
authors.initials: M
authors.lastname: Müller
mesh_terms: D019295:Computational Biology; D015180:Electrophoresis, Gel, Two-Dimensional; D029968:Escherichia coli Proteins / Q000737:chemistry*; D013058:Mass Spectrometry / Q000379:methods*
chemical_list: D029968:Escherichia coli Proteins