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Chebyshev acceleration of the GeneRank algorithm. (English) Zbl 1288.65036
Summary: The ranking of genes plays an important role in biomedical research. The GeneRank method of J. L. Morrison et al. [“GeneRank: Using search engine technology for the analysis of microarray experiments”, BMC Bioinformatics, No. 6, 233 (2005)] ranks genes based on the results of microarray experiments combined with gene expression information, for example from gene annotations. The algorithm is a variant of the well known PageRank iteration, and can be formulated as the solution of a large, sparse linear system. Here we show that classical Chebyshev semi-iteration can considerably speed up the convergence of GeneRank, outperforming other acceleration schemes such as conjugate gradients.

MSC:
65F10 Iterative numerical methods for linear systems
65F50 Computational methods for sparse matrices
68P10 Searching and sorting
92D10 Genetics and epigenetics
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