Method of miRNA function recognition based on multi-genomics

An identification method and function technology, applied in the field of bioinformatics, can solve the problem of low accuracy of miRNA function identification, and achieve the effect of high identification accuracy and sufficient theoretical basis

Inactive Publication Date: 2018-12-18
QIQIHAR UNIVERSITY
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  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to propose a method for miRNA function recognition based on mult

Method used

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  • Method of miRNA function recognition based on multi-genomics
  • Method of miRNA function recognition based on multi-genomics
  • Method of miRNA function recognition based on multi-genomics

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Experimental program
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specific Embodiment approach 1

[0017] Specific embodiment one: a method for identifying miRNA function based on multi-omics comprises the following steps:

[0018] Step 1: Calculate the gene P value through the gene expression profile, and select the differentially expressed genes, which are disease or drug-related genes;

[0019] Step 2: According to the differentially expressed genes selected in Step 1, construct a disease or drug-related protein network;

[0020] Step 3: Select functional modules from the disease or drug-related protein network constructed in step 2; the functional modules refer to subnetworks with significantly different overall expression levels in the protein network under disease or drug conditions;

[0021] Step 4: Perform enrichment analysis on the functional modules selected in Step 3 to determine the key genes in the functional modules;

[0022] Step 5: Analyzing differentially expressed miRNAs through miRNA expression profiling, and predicting target genes for differentially ex...

specific Embodiment approach 2

[0025] Specific embodiment two: the difference between this embodiment and specific embodiment one is: the specific process of selecting differentially expressed genes through gene expression profiles in the step one is:

[0026] Normal tissue was defined as pre-disease or pre-drug tissue, and normal conditions were pre-disease or pre-drug conditions. Normal tissue and disease- or drug-related tissue were used to carry out t-test, and the average expression level of a gene under normal conditions and disease- or drug-related conditions was set to be and no 1 and n 2 is the number of samples under normal conditions and under disease or drug-related conditions, and is the variance of the two samples, then the calculation of the t value is as follows:

[0027]

[0028] Calculate the P value based on the t value, and then set the threshold to select differentially expressed genes.

[0029] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0030] Embodiment 3: The difference between this embodiment and Embodiment 1 or 2 is that in Step 2, according to the differentially expressed genes selected in Step 1, the specific process of constructing a disease or drug-related protein network is as follows:

[0031] Differentially expressed gene S gene ={g 1 , g 2 ... g i}, i is the number of differentially expressed genes; the protein interaction network is defined as G=(V, E), V is the protein node, E is the interaction relationship between proteins, and the protein node V={v 1 , v 2 ,...v j}, j is the number of protein nodes; E={e 1 , e 2 ,... e t}, t is the protein network interaction coefficient, then the disease or drug-related protein interaction network is G S =(V S ,E S ), the node V of the disease or drug-related protein interaction network S and the interaction relationship E s defined as:

[0032] V S =V∩S gene

[0033] E. s ={e 1 , e 2 ,...e p}, and

[0034] where g 1 , g 2 ... g i...

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Abstract

The invention relates to a miRNA function recognition method based on multi-genomics, and relates to a miRNA function recognition method based on multi-genome. The present invention aims to solve theproblem of low accuracy of miRNA function recognition in the prior art. The method of the invention comprises: analyzing differentially expressed genes through gene expression profiles; constructing disease-or drug-related protein networks; selecting functional modules of the constructed protein network related to disease or drug; performing enrichment analysis of the selected functional modules to determine the key genes in the functional modules; analyzing differentially expressed miRNAs by miRNA expression profiles to predict the target genes of differentially expressed miRNAs; performing construction of miRNA-regulated disease-or drug-related protein networks; performing functional enrichment analysis on the nodal genes of the constructed miRNA-regulated disease or drug-related proteinnetwork to identify the function of miRNA. The invention is used in the field of bioinformatics.

Description

technical field [0001] The invention relates to the field of bioinformatics, in particular to a method for identifying miRNA functions based on multi-omics. Background technique [0002] Protein-protein interactions are an intrinsic property of biological processes, and protein-protein interaction networks explain fundamental cellular mechanisms. Protein Networks can map and integrate domain structure, post-translational modifications, interaction networks, and disease-associated proteins in the proteome. Expression profiling describes the gene expression type and abundance information of a specific cell or tissue in a specific state, and dynamically interprets information such as gene function, state, and environment. Integrates protein networks and gene expression profiling to mine multiple disease-associated cellular mechanisms. For example, Zhang "Roles of rifampicin in drug-drug interactions: underlying molecular mechanisms involving the nuclear pregnant Xreceptor" an...

Claims

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Application Information

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IPC IPC(8): G06F19/18G06F19/20
Inventor 王颖汝吉东
Owner QIQIHAR UNIVERSITY
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