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BACKGROUND Side effects are unwanted responses to drug treatment and are important resources for human phenotype information. The recent development of a database on side effects, the side effect resource (SIDER), is a first step in documenting the relationship between drugs and their side effects. It is, however, insufficient to simply find the association(More)
BACKGROUND The Swanson's ABC model is powerful to infer hidden relationships buried in biological literature. However, the model is inadequate to infer relations with context information. In addition, the model generates a very large amount of candidates from biological text, and it is a semi-automatic, labor-intensive technique requiring human expert's(More)
The Swanson's ABC model is powerful to infer hidden relationships buried in biological literatures. However, the model is inadequate to infer the relations with context information. In addition, the model generates very large amount of candidates from biological text, and it is the semi-automatic, labor intensive technique requiring human expert's input. In(More)
Network-based methods using molecular interaction networks integrated with gene expression profiles have been proposed to solve problems, which arose from smaller number of samples compared with the large number of predictors. However, previous network-based methods, which have focused only on expression levels of proteins, nodes in the network through the(More)
BACKGROUND Drug repositioning is the process of finding new indications for existing drugs. Its importance has been dramatically increasing recently due to the enormous increase in new drug discovery cost. However, most of the previous molecular-centered drug repositioning work is not able to reflect the end-point physiological activities of drugs because(More)
Computer-based virtual human model is believed to be the promising solution for drug response identification. Literature mining is competitive method to extract those biological rules for human model simulation, since existing public databases provide only limited amount of information applicable for the simulation. Here we propose the method for mining(More)
In this work, we propose a comprehensive analysis of the genomic features of the human in mutations to classify loss-of-function (LoF) and gain-of-function (GoF) mutations. Through these genetic mutations, a protein can lose its native function, or it can confer a new function. However, when a mutation occurs, it is difficult to determine whether it will(More)
The side effect of drugs often results from a response to the unintended target of a drug. Recently there have been researches identifying targets of known drugs based on the side effect information. These researches, however, did not consider the association of drugs both with targets and with biological processes. The recent development of a database of(More)
Somatic mutations in cancer genomes often show allelic imbalance (AI) of mutation abundance between the genome and transcriptome, but there is not yet a systematic understanding of AI. In this study, we performed large-scale DNA and RNA AI analyses of >100,000 somatic mutations in >2,000 cancer specimens across five tumor types using the exome and(More)