Inferring a biological network from a set of observed time series is becoming more important as technologies such as DNA microarrays have been developed rapidly in recent years. Many models have been proposed to describe the biological network. Among them is a system of differential equations, which is flexible to represent the complex relationships among their components. In most of the previo...

Background: Microarray experiments can simultaneously determine the expression of thousands of genes. Identification of potential genes from microarray data for diagnosis of cancer is important. This study aimed to identify genes for the diagnosis of acute myeloid and lymphoblastic leukemia using a sparse feature selection method. Materials and Methods: In this descriptive study, the expressio...

Observations of systematic gene perturbation experiments have been proven the most informative for the identification of regulatory relations between genes. For this purpose, we present a novel Qualitative Reasoning approach, based on a qualitative abstraction of DNA-microarray data and on a set of IF-THEN inference rules. Our algorithm exhibits an extremely low rate of false positives, competi...