On Extraction Algorithms of RNAs Characterizing a Correlation of Gene Expression Data

Abstract

Recently, in assessing harmful chemicals, low cost cell experiment has attracted a lot of attention as an alternative to animal experiment.Also in acquisition of gene expression data, it is able to acquire the large data more accurately since the next-generation sequencer is implemented. However, methods for analyzing gene expression data acquired by next-generation sequencer from cell experiment have not been established yet. In this study, we propose one of such method: a method to extract RNAs of characterizing a correlation of gene expression data. Specifically, Optimal problems for the correlation coefficients are given and the optimal solutions are acquired by the meta-heuristics. Information between gene expression data is summarized by the proposal method. The features of sets of RNAs are discussed and the effectiveness of the proposal method is evaluated through data experiments.