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A GPU-based Method for Computing Eigenvector Centrality of Gene-expression Networks

Ahmed Shamsul Arefin, Regina Berretta, Pablo Moscato
Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, School of Electrical Engineering and Computer Science, Faculty of Engineering and Built Environment, The University of Newcastle, Callaghan, NSW 2308, Australia
Parallel and Distributed Computing 2013 (AusPDC 2013), 2013

@article{arefin2013gpu,

   title={A GPU-based Method for Computing Eigenvector Centrality of Gene-expression Networks},

   author={Arefin, Ahmed Shamsul and Berretta, Regina and Moscato, Pablo},

   year={2013}

}

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In this paper, we present a fast and scalable method for computing eigenvector centrality using graphics processing units (GPUs). The method is designed to compute the centrality on gene-expression networks, where the network is pre-constructed in the form of kNN graphs from DNA microarray data sets.
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