Abstract
Discovering protein complexes in vivo is of vital importance to understand the evolution and function of biological systems. Proteomics analysis has evolved as a state-of-the-art technique in elucidating the above information. A combination of liquid chromatography (LC) and liquid chromatography coupled to shotgun mass spectrometry (LC-MS) provides the most exhaustive information in this regard. However, a significant amount of computational effort is required for the meaningful interpretation of the generated datasets. In this chapter we describe in detail the state-of-the-art pipeline to discover soluble protein complexes and provide practical advice focusing on typical situations a biologist faces while analyzing such proteomics datasets. Furthermore, we briefly describe two commonly used software packages to solve the described problem: Weka for training protein-protein interactions (PPIs) using machine learning (ML) and Cytoscape for clustering the interaction network.
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