Volume 41, pp. 179-189, 2014.

Polynomial Preconditioning for the GeneRank Problem

Davod Khojasteh Salkuyeh, Vahid Edalatpour, and Davod Hezari


Identifying key genes involved in a particular disease is a very important problem in biomedical research. The GeneRank model is based on the PageRank algorithm and shares many of its mathematical properties. The model brings together gene expression information with a network structure and ranks genes based on the results of microarray experiments combined with gene expression information, for example, from gene annotations (GO). In this study, we present a polynomial preconditioned conjugate gradient algorithm to solve the GeneRank problem and study its properties. Some numerical experiments are given to show the effectiveness of the suggested preconditioner.

Full Text (PDF) [457 KB], BibTeX

Key words

gene network, gene ontologies, conjugate gradient, Chebyshev polynomial, preconditioner, M-matrix

AMS subject classifications

65F10, 65F50, 9208, 92D20

Links to the cited ETNA articles

[4]Vol. 40 (2013), pp. 311-320 Michele Benzi and Verena Kuhlemann: Chebyshev acceleration of the GeneRank algorithm

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