Learn More
The initial genome-scale reconstruction of the metabolic network of Escherichia coli K-12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique(More)
Drug-induced liver injury (DILI) is a critical issue in drug development because DILI causes failures in clinical trials and the withdrawal of approved drugs from the market. There have been many attempts to predict the risk of DILI based on in vivo and in silico identification of hepatotoxic compounds. In the current study, we propose the in silico(More)
Enzymes are thought to have evolved highly specific catalytic activities from promiscuous ancestral proteins. By analyzing a genome-scale model of Escherichia coli metabolism, we found that 37% of its enzymes act on a variety of substrates and catalyze 65% of the known metabolic reactions. However, it is not apparent why these generalist enzymes remain.(More)
MOTIVATION For the early detection of cancer, highly sensitive and specific biomarkers are needed. Particularly, biomarkers in bio-fluids are relatively more useful because those can be used for non-biopsy tests. Although the altered metabolic activities of cancer cells have been observed in many studies, little is known about metabolic biomarkers for(More)
Understanding altered metabolism is an important issue because altered metabolism is often revealed as a cause or an effect in pathogenesis. It has also been shown to be an important factor in the manipulation of an organism's metabolism in metabolic engineering. Unfortunately, it is not yet possible to measure the concentration levels of all metabolites in(More)
BACKGROUND One of the most challenging problems in mining gene expression data is to identify how the expression of any particular gene affects the expression of other genes. To elucidate the relationships between genes, an association rule mining (ARM) method has been applied to microarray gene expression data. However, a conventional ARM method has a(More)
Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH), succinate dehydrogenase (SDH), and fumarate hydratase (FH) that produce oncometabolites that competitively(More)
Evolution results from molecular-level changes in an organism, thereby producing novel phenotypes and, eventually novel species. However, changes in a single gene can lead to significant changes in biomolecular networks through the gain and loss of many molecular interactions. Thus, significant insights into microbial evolution have been gained through the(More)
Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the(More)
BACKGROUND Lymph node invasion is one of the most powerful clinical factors in cancer prognosis. However, molecular level signatures of their correlation are remaining poorly understood. Here, we propose a new approach, monotonically expressed gene analysis (MEGA), to correlate transcriptional patterns of lymph node invasion related genes with clinical(More)