An enhanced topologically significant directed random walk in cancer classification using gene expression datasets.

ABSTRACT: Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias pro

SUBMITTER: Seah CS 

PROVIDER: S-EPMC5851940 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature