The invention relates to a
heuristic breadth-first searching method for
cancer-related genes. According to the method, appearance frequencies of genes in a selected
gene subset are used for measuring the genes, and genes with higher appearance frequency are considered as the most important
cancer-related genes, on the basis, a classifier is designed and a
gene ordering method based on HBSA is established. As proved by study, information
gene selection plays an important role in improving the classification performance, and the genes can be probably taken as important tumor
clinical diagnosis signs, so discovery of the minimum
gene subset with the highest classification performance is a very important research objective. As indicated by experimental results, the
heuristic breadth-first searching method can not only obtain favorable generalization performance but also discover important tumor genes. And the relationship of the appearance frequencies of the selected genes and the gene number conforms to power-law distribution. The genes in the
gene subset with extremely high classification accuracy are in
close relationship with specific tumor subtypes, and even the genes are important genes directly related with the tumor.