title: Testing and Validation of Computational Methods for Mass Spectrometry.
abstract: High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.
authors.affiliation: Computational Proteomics Unit and Cambridge Centre for Proteomics, University of Cambridge , Cambridge CB2 1QR, United Kingdom.
authors.forename: Laurent
authors.initials: L
authors.lastname: Gatto
authors.affiliation: Department of Biostatistics, Johns Hopkins University , Baltimore, Maryland 21205, United States.|Institute of Genetic Medicine, Johns Hopkins University , Baltimore, Maryland 21205, United States.
authors.forename: Kasper D
authors.initials: KD
authors.lastname: Hansen
authors.affiliation: Institute for Systems Biology , Seattle, Washington 98109, United States.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Hoopmann
authors.affiliation: European Bioinformatics Institute (EMBL-EBI) , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom.|National Center for Protein Sciences , Beijing, China.
authors.forename: Henning
authors.initials: H
authors.lastname: Hermjakob
authors.affiliation: Quantitative Biology Center, Universität Tübingen , Auf der Morgenstelle 10, 72076 Tübingen, Germany.|Center for Bioinformatics, Universität Tübingen , Sand 14, 72076 Tübingen, Germany.|Dept. of Computer Science, Universität Tübingen , Sand 14, 72076 Tübingen, Germany.|Biomolecular Interactions, Max Planck Institute for Developmental Biology , Spemannstr. 35, 72076 Tübingen, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher
authors.affiliation: CECAD, University of Cologne , 50931 Cologne, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Beyer
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods / Q000592:standards*; D013058:Mass Spectrometry / Q000379:methods*; D040901:Proteomics / Q000379:methods