Predicting Cancerous Genes based on Regular Truth Table

[[abstract]]Several of ten thousands functional genes control the growth, genetics, and behavior of living organisms by regulating different gene expressions. The genes in a normal cell control the process of cell growth, differentiation, reproduction, and apoptosis via multiple steps of interactive regulation mechanism. The mechanism of gene regulation is a very important process in human beings. If there is something wrong in the gene regulation mechanism, it may cause some diseases such as cancer. It is very difficult to identify the regulatory relations among genes in human genome. Traditional biological research methods consume huge amount of time and man strength to do this work. In recent years, with the rapid development of microarray technologies, cDNA can be used to analyze the changes of gene expressions in different cells in a high throughput manner. In this paper, we propose a novel bioinformatics approach to predict possible cancerous genes based on a so-called regulation truth table (RTT) of genes. The RTT of two genes is constructed using the differential expressions of cDNA microarray data for tumor and normal tissues. The differences in regulatory relations of genes for tumor and normal tissues are adopted to identify possible cancerous genes