Learn More
MOTIVATION The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to(More)
We have developed the fully-automated algorithms for processing 2-D gel electrophoretograms based on RLGS (restriction landmark genomic scanning) method; one for fully-automated spot recognition from RLGS electrophoretogram and another for fully-automated pairwise matching of the spots found on such 2-D electrophoretograms. Without any human interaction,(More)
We have developed a p owerful image processing system DNAinsight, which performs automated detection of several thousands of spots found on autoradiogram images obtained with 2-D gel elec-trophoresis of genomic DNA. Algorithms and parameters for detecting spot locations and intensities are c arefully chosen so as to enable reliable and rapid processing of(More)
BACKGROUND In our previous study, adrenomedullin (AM) overexpression could limit the arterial intimal hyperplasia induced by cuff injury in rats. However, it remains to be elucidated whether endogenous AM plays a role against vascular injury. METHODS AND RESULTS We used the AM knockout mice to investigate the effect of endogenous AM. Compared with(More)
We applied a method based on Akaike's information criterion (AIC) to detect genes whose expression profile is considerably different in some tissue(s) than in others. Such observations are detected as outliers, and the method we used was originally developed to detect outliers. The main advantage of the method is that objective decisions are possible(More)
We have developed the automated processing algorithms for 2-dimensional (2-D) electrophore-tograms of genomic DNA based on RLGS (Restriction Landmark Genomic Scanning) method, which scans the restriction enzyme recognition sites as the landmark and maps them onto a 2-D electrophoresis gel. Our powerful processing algorithms realize the automated spot(More)
random population of bit matrices is initialized at the beginning of the genetic algorithm run. A next population is obtained by applying the three genetic operations: selection, crossover and mutation. The selection operator is applied in order to choose matrices for the next generation from the matrices in the current population, where the selection(More)