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    An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome.

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    Authors
    Bitton, Danny A
    Smith, Duncan L
    Connolly, Yvonne
    Scutt, Paul J
    Miller, Crispin J
    Affiliation
    Applied Computational Biology and Bioinformatics Group, Cancer Research UK, Paterson Institute for Cancer Research, The University of Manchester, Manchester, United Kingdom.
    Issue Date
    2010
    
    Metadata
    Show full item record
    Abstract
    BACKGROUND: Most protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool. RESULTS: Using a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci. CONCLUSIONS: MS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.
    Citation
    An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome. 2010, 5 (1):e8949 PLoS ONE
    Journal
    PloS One
    URI
    http://hdl.handle.net/10541/109355
    DOI
    10.1371/journal.pone.0008949
    PubMed ID
    20126623
    Type
    Article
    Language
    en
    ISSN
    1932-6203
    ae974a485f413a2113503eed53cd6c53
    10.1371/journal.pone.0008949
    Scopus Count
    Collections
    All Paterson Institute for Cancer Research

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