DOI: 10.3724/SP.J.1206.2011.00311

Progress in Biochemistry and Biophysics (生物化学与生物物理进展) 2012/39:6 PP.581-590

A Novel Scale-free Network Construction Method and Its Application in Gene Expression Profiles Simulation*

In this paper, a novel scale-free network construction algorithm based on reconnection method was proposed. The regulatory node of the new node will be reselected according to the reconnection method. The probability of reconnection depends on the gamma in the power-law distribution model parameters. The constructed network with our algorithm was used for simulating gene expression profiles using differential equation model with two heuristic search algorithms, GA and PSO, and new algorithm GFA to optimize the criterion. The candidate old node can be selected as regulatory node based on the number of links the old node already has. The network in the experiment was testified using log-log graph. And the simulated gene expression profiles were also tested with three different well developed algorithms' software available free from internet by reconstructing the network. PPV and Se of the links were calculated and visualized. A part of the results and the full version program written by java could be downloaded from our website:

Key words:gene expression profiles, scale-free network, reconnection, differential equation, heuristic search algorithm

ReleaseDate:2014-07-21 16:18:47

Funds:This work was supported by grants from The National Natural Science Foundation of China (30900430, 30970932), The Project-sponsored by SRF for ROCS, SEM ([2010]1561), Ningbo Natural Science Foundation (2011A610065, 2009A610128), Innovative Research Team of Educational Commission of Zhejiang Province (T200907), Innovative Research Team of Ningbo (2009B21002), Disciplinarity Project of Ningbo University (XKL11D2114), Scientific Research Foundation of Graduate School of Ningbo University (G11JA029), Undergraduate Scientific and Technological Innovation Project (2010R405042) and The K.C.Wong Magna Fund in Ningbo University

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