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Reconstructing Models from Proteomics Data

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Computational Systems Neurobiology

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Abstract

The synaptic proteome is a highly complex and dynamic structure composed of more roughly 2,000 distinct proteins. The constant improvement of synaptic fraction preparation, protein complex isolation and mass spectrometry identification methods has led to a great accumulation of synaptic proteomics data. In order to gain a better insight of how the synaptic proteome is organised in molecular complexes identified from the biochemical analysis of neural tissues we have developed and combined a series of methods for reconstructing and analysing protein interaction network models from synaptic proteomics data. These methods cover every aspect of the reconstruction, ranging from how to annotate the proteins and acquire the protein interaction data to how to interpret and analyse the resulting models. This chapter gives a detailed overview of these methods as well as example applications to case study proteomics datasets.

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  1. School of Informatics, University of Edinburgh, Edinburgh, UK

    Lysimachos Zografos & J. Douglas Armstrong

  2. School of Medicine, Cardiff University, Cardiff, UK

    Andrew J. Pocklington

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    N. Le Novère

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Zografos, L., Pocklington, A.J., Armstrong, J.D. (2012). Reconstructing Models from Proteomics Data. In: Le Novère, N. (eds) Computational Systems Neurobiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3858-4_2

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