2015 Fiscal Year Final Research Report
Improving logic-based hypothesis-finding methods with inverse subsumption and its applications to systems biology
| Project/Area Number |
25730133
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | University of Yamanashi |
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Principal Investigator |
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| Research Collaborator |
MORIYA HISAO
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Keywords | 学習と知識獲得 / システム生物学 / 逆包摂法 / SBGN / 転写因子ネットワーク / 仮説推論 |
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| Outline of Final Research Achievements |
This research aims at improving logic-based hypothesis-finding methods and furthermore prompting to apply them to real problems in systems biology. First, we focus on so-called Inverse Subsumption (IS), which is a novel approach for finding hypotheses from observations with the background theory. Recently, it has been growing interests in IS to find such hypotheses that cannot be inherently obtained by the previously proposed approach. IS however has yet to achieve sufficient scalability in real problems. We consider to improve the two procedures of IS (dualization and subsumption-lattice search) in this research. Next, we focus on so-called SGBN, which is the standard markup language to describe molecular networks in systems biology. We establish an efficient way to translate SBGN into first-order logic (FOL). Together with SBGN-FOL translation, we apply hypothesis-finding methods to derive new knowledge in real SBGN-based molecular networks of cells.
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| Free Research Field |
総合領域
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