Abstract
Various strategies have been proposed for predicting protein function. They are derived from the classical homology-based approaches and emerging alternative approaches taking into account gene history in the framework of phylogenetic comparative methods. The growing numbers of available genome sequences and data require bioinformatics tools, in which methodological approaches are set according to the biological issues to be addressed. Much effort has already been devoted to integrating evolutionary biology into bioinformatics tools; e.g., homology-based functional annotation has been successfully integrated in a pipeline-assisted method. In addition, new concepts based on correlation of evolutionary events are emerging. For example, two independent events (e.g., systematic loss of specific genes) that happen repetitively can therefore be functionally linked. However, correlated gene profiles, also called “contextual annotation,” makes use of different bioinformatics resources based on multi-agent development. In this chapter, we describe evolutionary concepts and bioinformatics approaches proposed for future functional inference.
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Acknowledgments
This research was supported by the contract MIE (Maladies Infectieuses Emergentes-Programme Interdisciplinaire, CNRS) and ANR EvolHHuPro (ANR-07-BLAN-0054-01).
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Gouret, P. et al. (2011). Integration of Evolutionary Biology Concepts for Functional Annotation and Automation of Complex Research in Evolution: The Multi-Agent Software System DAGOBAH. In: Pontarotti, P. (eds) Evolutionary Biology – Concepts, Biodiversity, Macroevolution and Genome Evolution. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20763-1_5
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DOI: https://doi.org/10.1007/978-3-642-20763-1_5
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