Essential Protein Identification Based on Essential Protein-Protein Interaction Prediction by Integrated Edge Weights
Integrated Edge Weights (IEW) is a novel computational method to identify essential proteins. It works by ranking protein-protein interactions according to their integrated edge weights first, and then identified sub PPI networks consisting of those highly-ranked edges, and finally regarded the nodes in these sub networks as essential proteins. We evaluated IEW on three model organisms: Saccharomyces cerevisiae (S. cerevisiae), Escherichia coli (E. coli), and Caenorhabditis elegans (C. elegans). The experimental results showed that IEW achieved better performance than the state-of-the-art methods in terms of precision-recall and Jackknife measures. We had also demonstrated that IEW is a robust and effective method, which can retrieve biologically significant modules by its highly-ranked protein-protein interactions for S. cerevisiae, E. coli, and C. elegans. We believe that, with sufficient data provided, IEW can be used to any other organisms’ essential protein identification.
For each of the three datasets, top 100 ranked IEW edges and the proteins they connected are given for further verification and biological analysis.
|Top 100 ranked IEW edges & proteins information in S. cerevisiae||[download]|
|Top 100 ranked IEW edges & proteins information in E. coli||[download]|
|Top 100 ranked IEW edges & proteins information in C. elegans||[download]|
We have implemented matlab scripts for essential protein identification with IEW method. These scripts can be freely downloaded and modified for academic uses.
Yuexu Jiang, Yan Wang, Wei Pang, Liang Chen, Huiyan Sun, Yanchun Liang and Enrico Blanzieri, 2015, Essential Protein Identification Based on Essential Protein-Protein Interaction Prediction by Integrated Edge Weights. Submitted.
Contact: Yuexu Jiang, Yan Wang
Last update: 03/30/2015 by Yuexu Jiang.