Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics |
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Authors: | Damian Fermin Baxter B Allen Thomas W Blackwell Rajasree Menon Marcin Adamski Yin Xu Peter Ulintz Gilbert S Omenn David J States |
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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 |
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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. |
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