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Identification of Alternatively Spliced Transcripts Using a Proteomic Informatics Approach

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Data Mining in Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 696))

Abstract

We present the protocol for the identification of alternatively spliced peptide sequences from tandem mass spectrometry datasets searched using X!Tandem against our modified ECgene resource with all potential translation products and then matched with the Michigan Peptide to Protein Integration (MPPI) scheme. This approach is suitable for human and mouse datasets. Application of the method is illustrated with a study of the Kras activation-Ink4/Arf deletion mouse model of human pancreatic ductal adenocarcinoma.

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Author information

Authors and Affiliations

  1. Center for Computational Medicine and Biology and National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI, USA

    Rajasree Menon

  2. Departments of Medicine and Genetics, Center for Computational Medicine and Bioinformatics, Medical School and School of Public Health, University of Michigan, Ann Arbor, MI, USA

    Gilbert S. Omenn

Authors
  1. Rajasree Menon
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  2. Gilbert S. Omenn
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Editor information

Editors and Affiliations

  1. Lead Discovery Center GmbH, Emil-Figge-Straße 76a76a, Dortmund, 44227, Germany

    Michael Hamacher

  2. Medizinisches Proteom-Center, Ruhr-Universität Bochum, Universitätsstraße 150, Bochum, 44801, Germany

    Martin Eisenacher

  3. Medizinisches Proteom-Center, Ruhr-Universität Bochum, Universitätsstraße 150, Bochum, 44801, Germany

    Christian Stephan

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© 2011 Springer Science+Business Media, LLC

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Menon, R., Omenn, G.S. (2011). Identification of Alternatively Spliced Transcripts Using a Proteomic Informatics Approach. In: Hamacher, M., Eisenacher, M., Stephan, C. (eds) Data Mining in Proteomics. Methods in Molecular Biology, vol 696. Humana Press. https://doi.org/10.1007/978-1-60761-987-1_20

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  • DOI: https://doi.org/10.1007/978-1-60761-987-1_20

  • Published:

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60761-986-4

  • Online ISBN: 978-1-60761-987-1

  • eBook Packages: Springer Protocols

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