Triple network resource propagating method
A network resource and network technology, applied in the field of bioinformatics, can solve problems such as limiting the selection of prediction methods
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2017-07-07
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
Description
technical field
[0001] The invention relates to bioinformatics, in particular to a tripartite network resource dissemination method. The association relationship between lncRNA and environmental factors can be obtained. Background technique
[0002] The debate on whether variation in biological traits is congenital or acquired is mainly due to the debate on whether the variation is caused by genetic differences or environmental differences. The current main scientific point of view is that phenotypic differences are not caused by individual genetic differences or environmental differences, but are determined by the mutual influence of the two. This means that phenotypes and diseases are considered to be determined by a complex interplay between genetic factors (GFs) and environmental factors (EFs). To this day, it is generally accepted that almost all disease is the result of complex interactions between an individual's genetic makeup and their respective environments. So...
Examples
Embodiment Construction
[0031] Combine below Figure 1 to Figure 3 The present invention is further described.
[0032] In the transfer model of the tripartite network, it is actually a process in which resources are transferred and superimposed on each node. For the processed bipartite graph N lm =(V l ,V m ,E lm ) and N me =(V m ,V e ,E me ) to construct the adjacency matrix respectively and where in the bipartite graph N lm in, if and interrelated, then otherwise In bipartite graph N me There is a similar definition in , if and interrelated, then otherwise
[0033] The resource transfer process of the tripartite network resource transfer algorithm is actually the weighting process of projecting a bipartite graph onto the tripartite network, that is, based on the intermediate miRNA, the weighting of the unilateral projection on the lncRNA-miRNA and miRNA-EF networks. Therefore, the algorithm can be divided into three parts, that is, to calculate the unilateral project...