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Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics
Authors:Damian Fermin  Baxter B Allen  Thomas W Blackwell  Rajasree Menon  Marcin Adamski  Yin Xu  Peter Ulintz  Gilbert S Omenn  David J States
Institution:(1) Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA;(2) Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA;(3) Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
Abstract:

Background  

Defining the location of genes and the precise nature of gene products remains a fundamental challenge in genome annotation. Interrogating tandem mass spectrometry data using genomic sequence provides an unbiased method to identify novel translation products. A six-frame translation of the entire human genome was used as the query database to search for novel blood proteins in the data from the Human Proteome Organization Plasma Proteome Project. Because this target database is orders of magnitude larger than the databases traditionally employed in tandem mass spectra analysis, careful attention to significance testing is required. Confidence of identification is assessed using our previously described Poisson statistic, which estimates the significance of multi-peptide identifications incorporating the length of the matching sequence, number of spectra searched and size of the target sequence database.
Keywords:
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