LncRNA and disease association relationship prediction method and system based on Naive Bayes
A technology of correlation relationship and prediction method, applied in the field of correlation prediction in bioinformatics, can solve the problems of high equipment requirements, high cost, long experimental period, etc., and achieve the effect of reducing workload and improving prediction effect.
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Embodiment 1
[0036] see figure 1 , the Naive Bayesian-based LncRNA and disease association prediction method of the present embodiment, comprising the following steps:
[0037] S1: Construct a complex network based on the relationship between MiRNA and disease, MiRNA and LncRNA, and LncRNA and disease based on the known data sets. Step S1 comprises the following steps:
[0038] S101: Download from multiple known databases: the relationship between MiRNA and disease and the relationship between MiRNA and LncRNA;
[0039] Delete duplicate data and erroneous data in the data set of the relationship between MiRNA and disease and the relationship between MiRNA and LncRNA.
[0040] S102: first unify the nomenclature of MiRNA, LncRNA and disease from different databases. Screen out the common MiRNA set in the relationship between MiRNA and disease and the relationship between MiRNA and LncRNA, and extract the relationship between common MiRNA and disease and the relationship between common MiR...
Embodiment 2
[0048] figure 2 It is a schematic flow chart of the naive Bayesian-based LncRNA-disease association prediction method in this embodiment, wherein: (A) collects and organizes the association relationship between MiRNA and disease from the three databases of HMDD, starBase and MNDR respectively , the relationship between MiRNA and LncRNA and the relationship between LncRNA and disease; (B) to construct a complex network by integrating the relationship between MiRNA and disease, the relationship between MiRNA and LncRNA and the relationship between LncRNA and disease; (C) The network to be predicted is constructed by expressing the network in the form of an adjacency matrix; (D) Calculate the similarity value of the final lncRNA-disease node pair based on the contribution of different neighbor nodes.
[0049] The naive Bayesian-based LncRNA and disease association prediction method of the present embodiment comprises the following steps:
[0050] (1) Sorting and screening of da...
Embodiment 3
[0088] The Naive Bayesian-based LncRNA-disease association prediction system of the present invention includes a memory, a processor, and a computer program stored on the memory and operable on the processor, and any of the above-mentioned methods is implemented when the processor executes the computer program A step of.
[0089] In summary, the present invention builds a complex network by integrating LncRN-MiRNA, disease-MiRNA, and LncRNA-disease associations, and then considers the association of the common neighbors (MiRNAs) nodes of the LncRNA-disease node pair in the network to the node pair Finally, based on the probability model of Naive Bayes, the prediction method is regarded as the probability that each neighbor node of the LncRNA node and the disease node will be connected to them. On the one hand, the naive Bayesian classifier is a very simple classifier with low computational complexity. On the other hand, the present invention is not entirely based on the known ...
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