Title:
METHOD AND SYSTEM FOR KNOWLEDGE-BASED ASSESSMENT OF DEPENDENCY RELATION NETWORK DISTINCTIVENESS
Document Type and Number:
WIPO Patent Application WO/2020/054936
Kind Code:
A1
Abstract:
The present invention relates to a method and system for knowledge-based assessment of dependency relation network distinctiveness and, more specifically, to a method and system for assessing dependency relation network distinctiveness, whereby, in a simulation to research genetic interrelation by using the assessment of dependency relation network distinctiveness of a gene set, time for the simulation can be reduced and the accuracy of simulation results can be improved, on the basis of existing knowledge. The disclosed method comprises the steps of: receiving a gene set containing a plurality of genes configured to be under a plurality of conditions; assessing each of the genes as a discrete random variable; selecting dependency network structures without certain genetic interrelations from network structures included in data on interrelations between genes, among all the plurality of dependency network structures constructible with the plurality of genes, for each of the conditions; calculating probability distributions of the selected dependency network structures for each of the conditions; calculating overall dependency relation network distinctiveness between the genes in the configured target gene set across the plurality of conditions, by calculating differences between the probability distributions of each of the network structures; and identifying a plurality of biological functions and pathways expressing genetic relations across the plurality of conditions, by using the overall dependency relation network distinctiveness.
Inventors:
JUNG SUNGWON (KR)
Application Number:
PCT/KR2019/004050
Publication Date:
March 19, 2020
Filing Date:
April 05, 2019
Export Citation:
Assignee:
JUNG SUNGWON (KR)
International Classes:
G16B40/00; G16B5/00; G16B20/00
Foreign References:
| US20140195165A1 | 2014-07-10 | |||
| US20080015788A1 | 2008-01-17 | |||
| KR20160132223A | 2016-11-17 |
Other References:
ZHANG, B.: "Differential dependency network analysis to identify condition-specific topological changes in biological networks", BIOINFORMATICS, 15 February 2009 (2009-02-15), pages 526 - 532, XP055696027
VAN DEN BULCKE, T.: "SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms", BMC BIOINFORMATICS, vol. 43, 26 January 2006 (2006-01-26), pages 1 - 12, XP021013933
VAN DEN BULCKE, T.: "SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms", BMC BIOINFORMATICS, vol. 43, 26 January 2006 (2006-01-26), pages 1 - 12, XP021013933
Attorney, Agent or Firm:
LEE, Won Hee (KR)
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