Shigeto Seno

Learn More
BACKGROUND Peritoneal relapse is the most common pattern of tumor progression in advanced gastric cancer. Clinicopathological findings are sometimes inadequate for predicting peritoneal relapse. The aim of this study was to identify patients at high risk of peritoneal relapse in a prospective study based on molecular prediction. METHODS RNA samples from(More)
The S-system model is one of the nonlinear differential equation models of gene regulatory networks, and it can describe various dynamics of the relationships among genes. If we successfully infer rigorous S-system model parameters that describe a target gene regulatory network, we can simulate gene expressions mathematically. However, the problem of(More)
Both large deletions in genome and heat shock stress would lead to alterations in the gene expression profile; however, whether there is any potential linkage between these disturbances to the transcriptome have not been discovered. Here, the relationship between the genomic and environmental contributions to the transcriptome was analyzed by comparing the(More)
Recently, gene expression data under various conditions have largely been obtained by the utilization of the DNA microarrays and oligonucleotide arrays. There have been emerging demands to analyze the function of genes from the gene expression profiles. For clustering genes from their expression profiles, hierarchical clustering has been widely used. The(More)
A simple mode of gene expression scaled by the distance from the chromosomal location of the gene to the genome replication site oriC was determined. The common formula representing the effect of genomic position on expression capacity not only supports the multifork replication model but also provides a base correlation for theoretical simulation and(More)
In this study, we investigated the effects of interleukin-1β (IL-1β), a typical proinflammatory cytokine on the β-adrenoreceptor-stimulated induction of uncoupling protein 1 (UCP1) expression in adipocytes. IL-1β mRNA expression levels were upregulated in white adipose tissues of obese mice and in RAW264.7 macrophages under conditions designed to mimic(More)
Bayesian networks (BNs) have been widely used to estimate gene regulatory networks. Many BN methods have been developed to estimate networks from microarray data. However, two serious problems reduce the effectiveness of current BN methods. The first problem is that BN-based methods require huge computational time to estimate large-scale networks. The(More)
With the advancement of genome research, it is becoming clear that genes are not distributed on the genome in random order. Clusters of genes distributed at localized genome positions have been reported in several eukaryotes. Various correlations have been observed between the expressions of genes in adjacent or nearby positions along the chromosomes(More)
BACKGROUND Identifying the differences between gene regulatory networks under varying biological conditions or external stimuli is an important challenge in systems biology. Several methods have been developed to reverse-engineer a cellular system, called a gene regulatory network, from gene expression profiles in order to understand transcriptomic behavior(More)
In bacteria, cell size affects chromosome replication, the assembly of division machinery, cell wall synthesis, membrane synthesis and ultimately growth rate. In addition, cell size can also be a target for Darwinian evolution for protection from predators. This strong coupling of cell size and growth, however, could lead to the introduction of growth(More)