Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/36267
Title: A highly efficient approach to protein interactome mapping based on collaborative filtering framework
Authors: Luo, X
You, ZH
Zhou, MC
Li, S 
Leung, H 
Xia, YN
Zhu, QS
Issue Date: 2015
Publisher: Nature Publishing Group
Source: Scientific reports, 2015, v. 5, 7702 How to cite?
Journal: Scientific reports 
Abstract: The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.
URI: http://hdl.handle.net/10397/36267
EISSN: 2045-2322
DOI: 10.1038/srep07702
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