POLYNOMIAL PRECONDITIONING FOR THE GENERANK PROBLEM

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.