Quantitative Biology > Biomolecules
[Submitted on 8 Jul 2021 (v1), last revised 6 Feb 2022 (this version, v4)]
Title:Network and Sequence-Based Prediction of Protein-Protein Interactions
View PDFAbstract:Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem. Experimental methods are slow, expensive, and may be error prone.Many computational methods have been proposed to identify candidate interacting pairs. When accurate, they can serve as an inexpensive, preliminary filtering stage, to be followed by downstream experimental validation. Among such methods, sequence-based ones are very promising.Results:We present, a new algorithm that leverages both topological and biological information to predict protein-protein interactions. We comprehensively compare our Framework with state-of-the-art approaches on reliable PPIs datasets, showing that they have competitive or higher accuracy on biologically validated test sets.Conclusion:We shown that topological plus sequence-based computational methods can effectively predict the entire human interactome compared with methods that leverage only one source of biological information.
Submission history
From: Leonardo Martini [view email][v1] Thu, 8 Jul 2021 09:16:46 UTC (755 KB)
[v2] Wed, 29 Sep 2021 10:45:11 UTC (24,419 KB)
[v3] Thu, 11 Nov 2021 14:06:08 UTC (13,883 KB)
[v4] Sun, 6 Feb 2022 17:21:18 UTC (8,760 KB)
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