New Approaches to Mechanism Analysis for Drug Discovery Using DNA Microarray Data Combined with KeyMolnet

Hiromi      Sato; Seiichi      Ishida; Kyoko      Toda; Rieko      Matsuda; Yuzuru      Hayashi; Makoto      Shigetaka; Miki      Fukuda; Yohko      Wakamatsu; Akiko      Itai

doi:10.2174/1570163054064701

Abstract

We have developed a comprehensive information platform, named KeyMolnet, for drug discovery and life science research in the post-genome era. Using KeyMolnet, we show new approaches to research into the biological mechanism in DNA microarray analysis. Thanks to the DNA microarray technology, it is now possible to obtain very large quantities of gene expression data at a time. However, it is still difficult to extract meaningful information from such large quantities of data and to analyze the relationship between gene expression data and biological function. We therefore developed an advanced tool that can generate molecular networks upon demand, and beyond signaling “cross-talks,” can connect them to physiological phenomena and medical and drug information. Here we show the methods of mechanism analysis using the DNA microarray data and KeyMolnet, as well as the possible mechanism of inducing apoptosis in the human promyelocytic leukemia cell line, HL-60, treated with 12-O-tetradecanoylphorbol 13-acetate (TPA), using the time series of gene expression data from DNA microarray experiments. KeyMolnet enables practical approaches to research into biological mechanisms, which in turn contribute to new discoveries in the medical, pharmaceutical and life sciences.

Keywords: dna microarray, proteomics, network, molecular relation, data mining, platform, apoptosis