DocumentCode
3196063
Title
Characterisation of protein-protein interaction network base on ℓ1-norm optimisation
Author
Li, Benjamin Y. S. ; Lam Fat Yeung ; Choujun Zhan ; Genke Yang
Author_Institution
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China
fYear
2013
fDate
18-21 Dec. 2013
Firstpage
509
Lastpage
512
Abstract
Knowledge of interactions between proteins is an importance piece of information on the understanding of cellular mechanism. One of the challenges is to quantify how similar the two protein-protein interaction (PPI) networks. To provide a candidate solution of this problem, a distance measure for PPI networks is proposed. This distance measure involves solving an optimisation problem with which the objective function being a weighted sum of topological and biological measure of an alignment respectively. To solve this problem, the projected subgradient method is employed. To illustrate the performance and usage of this distance measure, it is applied to the PPI networks of herpesvirus family. Five herpesviruses: EpsteinBarr virus (EBV), Herpes simplex virus (HSV), Mouse Cytomegalovirus (mCMV), Kaposi´s sarcoma-associated herpesvirus (KSHV) and Varicella zoster virus (VZV) are considered in this paper. PPI network distances of the five her-pesviruses are computed and visualized using multidimensional scaling (MDS). Results show that the distance measure can reflect the dissimilarity among organisms. In addition our algorithm can also separate herpesvirus subfamilies given only topological information of the PPI network.
Keywords
cellular biophysics; gradient methods; microorganisms; molecular biophysics; optimisation; proteins; ℓ1-norm optimisation; EBV; EpsteinBarr virus; HSV; Herpes simplex virus; KSHV; Kaposi sarcoma-associated herpesvirus; MDS; Mouse Cytomegalovirus; PPI networks; VZV; Varicella zoster virus; biological measurement; cellular mechanism; herpesvirus family; mCMV; multidimensional scaling; optimisation problem; projected sub-gradient method; protein-protein interaction network; topological information; topological measurement; Educational institutions; Genetics; Network topology; Optimization; Phylogeny; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location
Shanghai
Type
conf
DOI
10.1109/BIBM.2013.6732547
Filename
6732547
Link To Document