Learn More
BACKGROUND Interactions between biological entities such as genes, proteins and metabolites, so called pathways, are key features to understand molecular mechanisms of life. As pathway information is being accumulated rapidly through various knowledge resources, there are growing interests in maintaining the integrity of the heterogeneous databases. (More)
Interactions between biological entities such as genes, proteins and metabolites, so called pathways, are key features to understand molecular mechanisms of life. As pathway information is being accumulated rapidly through various knowledge resources, there are growing interests in maintaining integrity of the heterogeneous databases. Here, we defined(More)
Multi-compound drugs are considered as the most promising solution to overcome the limited efficacy and off-target effect of drugs. However, identifying promising multiple compounds by experimental tests requires overwhelming costs and a number of tests. Systems biology-based approaches are regarded as one of the most promising strategy. To predict(More)
MOTIVATION Complex physiological relationships exist among human diseases. Thus, the identification of disease associations could provide new methods of disease care and diagnosis. To this end, numerous studies have investigated disease associations. However, combinatorial effect of physiological factors, which is the main characteristic of biological(More)
Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and molecular pathways, most of previous(More)
Construction of a virtual physiological human system by reconstructing biological networks is proposed as an alternative to traditional drug development process. In silico methods using biological networks in human have been used for resolving current issues of traditional drug discovery like high costs and low success rates. However, most of previous(More)
Inferring novel findings from known biological knowledge is one of the ultimate goals in systems and network biology. There have been a number of computational methods to analyze quantitative/qualitative traits of biomedical networks. However, a genome-wide observation of a molecular and system level response to a given perturbation is hardly explored due(More)
Inferring drug-induced phenotypes via computational approaches can give a substantial support to drug discovery procedure. However, existing computational models that are mainly based on a single cell or a single organ model are thought to be limited because the phenotypes are consequences of stochastic biochemical processes among distant cells/organs as(More)
  • 1