Incorporating correlations among gene ontology terms into predicting protein functions

One of the key issues in the post-genomic era is to assign functions to uncharacterized proteins. Since proteins seldom act alone, but rather interact with other biomolecular units to execute their functions, the functions of unknown proteins may be discovered through studying their associations with proteins having known functions. In this chapter, the authors discuss possible approaches to exploit protein interaction networks for automated prediction of protein functions. The major focus is on discussing the utilities and limitations of current algorithms and computational techniques for accurate computational function prediction. The chapter highlights the challenges faced in this task and explores how similarity information among different gene ontology (GO) annotation terms can be taken into account to enhance function prediction. The authors describe a new strategy that has better prediction performance than previous methods, which gives additional insights about the importance of the dependence between functional terms when inferring protein function.