| Literature DB >> 25479794 |
Sanghamitra Bandyopadhyay, Sumanta Ray, Anirban Mukhopadhyay, Ujjwal Maulik.
Abstract
The computational or in silico approaches for analysing the HIV-1-human protein-protein interaction (PPI) network, predicting different host cellular factors and PPIs and discovering several pathways are gaining popularity in the field of HIV research. Although there exist quite a few studies in this regard, no previous effort has been made to review these works in a comprehensive manner. Here we review the computational approaches that are devoted to the analysis and prediction of HIV-1-human PPIs. We have broadly categorized these studies into two fields: computational analysis of HIV-1-human PPI network and prediction of novel PPIs. We have also presented a comparative assessment of these studies and proposed some methodologies for discussing the implication of their results. We have also reviewed different computational techniques for predicting HIV-1-human PPIs and provided a comparative study of their applicability. We believe that our effort will provide helpful insights to the HIV research community.Entities:
Keywords: HIV dependency factor; HIV-1-human PPI Network; association rule mining; biclustering; computational PPI prediction; random forest classifier; rank aggregation; semi supervised classification; topological properties of network
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Year: 2014 PMID: 25479794 DOI: 10.1093/bib/bbu041
Source DB: PubMed Journal: Brief Bioinform ISSN: 1467-5463 Impact factor: 11.622