2012 Fiscal Year Annual Research Report
計算アプローチによる肝炎の病態・治療に関する分子機構の解明
| Project/Area Number |
23300105
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| Research Institution | Japan Advanced Institute of Science and Technology |
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Principal Investigator |
TU・BAO Ho 北陸先端科学技術大学院大学, 知識科学研究科, 教授 (60301199)
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| Co-Investigator(Kenkyū-buntansha) |
神田 達郎 千葉大学, 医学(系)研究科(研究院), 講師 (20345002)
河崎 さおり 北陸先端科学技術大学院大学, 先端領域社会人教育院, 特任准教授 (40377437)
DAM HieuChi 北陸先端科学技術大学院大学, 知識科学研究科, 准教授 (70397230)
横須賀 收 千葉大学, 医学(系)研究科(研究院), 教授 (90182691)
高林 克日己 千葉大学, 医学部附属病院, 教授 (90188079)
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| Project Period (FY) |
2011-04-01 – 2014-03-31
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| Keywords | data mining / machine learning / hepatitis C virus / epigenetics / siRNA / hepatitis pathogenesis |
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| Research Abstract |
In this period of the research project we aimed at establishing a calculation approach based on techniques of data mining and machine learning for various biomedical data sources. Concretely, we work to contribute to the studies of the molecular mechanisms in the treatment and pathogenesis of hepatitis: (1) the resistance mechanisms of hepatitis C virus to the standard treatment by combination of interferon (IFN) and ribavirin (RBV) for therapy (HCV) in the NS5A protein, (2) the interaction of various factors between epigenetics and hepatitis progression, and (3) the prediction of efficacy of small interfering RNA (siRNA) in disease gene silence. In addition, we consider the study on the effect of these on each other, and provide a therapeutic effect improvement in the end as molecular biological basis, and promote understanding of the pathogenesis and treatment of hepatitis by quantitative analysis of the factors, for example the combination therapy to show how to improve the efficiency.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
In this period, among the three targeted problems, we achieved good result and progress on the first one of understanding the molecular resistance mechanisms of hepatitis C virus in NS5A to the combination of interferon (IFN) and ribavirin (RBV). We also made significant advancement on the third problem of siRNA by developping a method the learn the design rules for effective siRNA from the available scored siRNA sequences. We received less result on the second problem on the relationships between epigenetics factors and hepatitis progression that mostly caused by the lack of experimental data for computation.
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| Strategy for Future Research Activity |
For the first problem, we will revise and improve the programs and install it as a system. We will continue to learn and detect more descriminative motifs newly provided by hospitals. For the second problem, we will continue to apply our developed methods to the datasets about epigenetic factors in hepatitis in order to have insights on this research direction. For the third problem, we will focus on improving our methods of enriching the siRNA sequences and linear tensor regression. We also work on generating siRNA with highest knockdown efficacy and the evaluation of medical doctors at Chiba University Hospital.
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[Journal Article] Platelet count and sustained virological response in hepatitis C treatment2013
Author(s)
Tatsuo Kanda, Keizo Kato, Akihito Tsubota, Nobuo Takada, Takayoshi Nishino, Shigeru Mikami, Tatsuo Miyamura, Daisuke Maruoka, Shuang Wu, Shingo Nakamoto, Makoto Arai, Keiichi Fujiwara, Fumio Imazeki, Osamu Yokosuka
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Journal Title
World journal of hepatology
Volume: 5(4)
Pages: 182-188
Peer Reviewed
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[Presentation] From Clinical to Genomics Data in Hepatitis Study2012
Author(s)
Ho, T.B., Takabayashi, T., Kanda, T., Kawasaki, S., Le, T.N., Bui, N.T., Than, Q.K.
Organizer
The First Asian Conference on Information Systems
Place of Presentation
SiemRiep, Cambodia
Year and Date
20121206-20121208
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