Publications by authors named "Yusuke Komiyama"

Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor whose expression level is positively correlated with tumor aggressiveness and metastatic potential. However, the mechanism underlying SLPI-induced enhancement of malignant phenotype is not completely understood. The malignancy of cancer cells is highly dependent on cell migration activity.

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Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and sugars. In this study, we classified sugars into acidic and nonacidic sugars and showed that their binding sites have different amino acid occurrence frequencies.

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Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor that diminishes tissue destruction during inflammation. A recent report revealed high levels of SLPI expression in the oral carcinoma cell. In addition, overexpression of SLPI up-regulates metastasis in lung carcinoma cells.

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Motivation: Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful.

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Human stem cells are promising sources for regenerative therapy. To ensure safety of future therapeutic applications, the differentiation potency of stem cells has to be tested and be widely opened to the public. The potency is generally assessed by teratoma formation comprising differentiated cells from all three germ layers, and the teratomas can be inspected through high-quality digital images.

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Receptor tyrosine kinases are essential proteins involved in cellular differentiation and proliferation in vivo and are heavily involved in allergic diseases, diabetes, and onset/proliferation of cancerous cells. Identifying the interacting partner of this protein, a growth factor ligand, will provide a deeper understanding of cellular proliferation/differentiation and other cell processes. In this study, we developed a method for predicting tyrosine kinase ligand-receptor pairs from their amino acid sequences.

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Polymeric immunoglobulin receptor (pIgR) plays an important role in mucosal immune systems. Secretory immunoglobulin A, composed of secretory component of pIgR and a dimeric form of immunoglobulin A, is secreted on mucosal surfaces and serves as a biological defense factor. pIgR gene expression is reportedly induced by activation of the transcription factor nuclear factor (NF)-κB.

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Recently, earthworms have become a useful model for research into the immune system, and it is expected that results obtained using this model will shed light on the sophisticated vertebrate immune system and the evolution of the immune response, and additionally help identify new biomolecules with therapeutic applications. However, for earthworms to be used as a genetic model of the invertebrate immune system, basic molecular and genetic resources, such as an expressed sequence tag (EST) database, must be developed for this organism. Next-generation sequencing technologies have generated EST libraries by RNA-seq in many model species.

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The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data.

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To effectively treat serious bone defects using bone-regenerative medicine, a small chemical compound that potently induces bone formation must be developed. We previously reported on the osteogenic effect of 4-(4-methoxyphenyl)pyrido[40,30:4,5]thieno[2,3-b]pyridine-2-carboxamide (TH), a helioxanthin-derivative, in vitro. Here, we report on TH's osteogenic effects ex vivo and in vivo.

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To effectively treat bone diseases using bone regenerative medicine, there is an urgent need to develop safe and cheap drugs that can potently induce bone formation. Here, we demonstrate the osteogenic effects of icariin, the main active compound of Epimedium pubescens. Icariin induced osteogenic differentiation of preosteoblastic cells.

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To effectively treat serious bone defects using bone regenerative medicine, there is a need for the development of a small chemical compound that potently induces bone formation. We now report a novel osteogenic helioxanthin-derivative, TH. TH induced osteogenic differentiation in MC3T3-E1 cells, mouse primary osteoblasts, and mouse embryonic stem cells.

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