title: Reproducible quantitative proteotype data matrices for systems biology.
abstract: Historically, many mass spectrometry-based proteomic studies have aimed at compiling an inventory of protein compounds present in a biological sample, with the long-term objective of creating a proteome map of a species. However, to answer fundamental questions about the behavior of biological systems at the protein level, accurate and unbiased quantitative data are required in addition to a list of all protein components. Fueled by advances in mass spectrometry, the proteomics field has thus recently shifted focus toward the reproducible quantification of proteins across a large number of biological samples. This provides the foundation to move away from pure enumeration of identified proteins toward quantitative matrices of many proteins measured across multiple samples. It is argued here that data matrices consisting of highly reproducible, quantitative, and unbiased proteomic measurements across a high number of conditions, referred to here as quantitative proteotype maps, will become the fundamental currency in the field and provide the starting point for downstream biological analysis. Such proteotype data matrices, for example, are generated by the measurement of large patient cohorts, time series, or multiple experimental perturbations. They are expected to have a large effect on systems biology and personalized medicine approaches that investigate the dynamic behavior of biological systems across multiple perturbations, time points, and individuals.
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, CH-8093 Zurich, Switzerland Department of Genetics, Stanford University, Stanford, CA 94305.
authors.forename: Hannes L
authors.initials: HL
authors.lastname: Röst
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, CH-8093 Zurich, Switzerland S3IT, University of Zurich, CH-8057 Zurich, Switzerland.
authors.forename: Lars
authors.initials: L
authors.lastname: Malmström
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, CH-8093 Zurich, Switzerland Faculty of Science, University of Zurich, CH-8057 Zurich, Switzerland aebersold@imsb.biol.ethz.ch.
authors.forename: Ruedi
authors.initials: R
authors.lastname: Aebersold
mesh_terms: D019295:Computational Biology / Q000379:methods / Q000592:standards; D000068598:Data Accuracy; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods; D040901:Proteomics / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results; D049490:Systems Biology / Q000592:standards*