2013 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 / interferon/vibavirin / hepatitis pathogenesis / HCV / siRNA / epigenetics |
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| Research Abstract |
In this period of the research project we aimed at completing the work of the project on the computational approach based on techniques of data mining and machine learning for hepatitis study. For the targeted problems of the project, the achievements are as follows:
1. On HCV NS5A resistance mechanisms to interferon/ribavirin therapy: We established a semi-supervised learning methods to learn discriminative motifs in the protein NS5A of hepatitis C virus genome. We found different significant motifs that well distinguish two cases of response and non-response to the standard treatment by combination of interferon (IFN) and ribavirin (RBV).
2. On interplay between epigenetic factors in hepatitis progression: We succeeded in developing a nucleosomal method to inferring causal relationships of histone modifications that lead to chance to study the relationship between these two fields.
3. Selection of potent siRNAs for silencing hepatitis viruses: We succeeded in developing an advanced learning method that exploits available scored and labelled siRNAs obtained by experiments from laboratories. The method enrich the poor representation of siRNA and predict the knockdown efficacy of by an improved tensor regression technique.
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| Current Status of Research Progress |
Reason
25年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
25年度が最終年度であるため、記入しない。
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Research Products
(9 results)
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[Journal Article] Data mining for materials design: A computational study of suingle molecule magnet2014
Author(s)
Dam, H.C., Pham, T.L., Ho, T.B., Nguyen, T.A., Nguyen, V.C.
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Journal Title
The journal of Chemical Physics
Volume: Vol. 40, Issue 4
Pages: 400101-1
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