Abstract
Since protein interactions are at the basis of all cellular processes, knowing the interaction network around a protein of interest provides a lot of information on its functioning. It also allows inferring the function of hypothetical proteins, based on those of their interactors. On a larger scale, knowing the whole interactome of a given organism allows studying its biology from a systemic perspective, a tactic which is increasingly more used, for example, to approach diseases. Together with the time-consuming, expensive, and error-prone experimental methods for determining protein interactions, there are a number of computational approaches that are now often used as a complement for the first. They can, for example, target proteins difficult for the experimental techniques or simply provide additional evidences of interaction. These methodologies are mature enough, both in terms of accuracy and easiness of usage to be incorporated into the standard toolboxes of molecular biologists.
The protocols below describe in detail the practical usage of two web-based tools for predicting protein interactions from raw sequence information. These tools provide predictions based on different approaches, whose eventual agreement provides additional support for the predictions.
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Pazos, F., de Juan, D. (2015). Predicting Protein Interactions. In: McGenity, T., Timmis, K., Nogales Fernández, B. (eds) Hydrocarbon and Lipid Microbiology Protocols. Springer Protocols Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/8623_2015_113
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DOI: https://doi.org/10.1007/8623_2015_113
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