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Protein-protein interaction network based gene set identification method

A protein interaction and identification method technology, applied in the field of gene set identification based on protein-protein interaction network, can solve the problems that can not be ignored, lost significant modulation genes/proteins, etc.

Active Publication Date: 2014-12-03
SHANGHAI PUBLIC HEALTH CLINICAL CENT
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AI Technical Summary

Problems solved by technology

Analysis based on direct interactions of significantly regulated genes / proteins may lead to loss of those significantly regulated genes / proteins that interact indirectly through key node genes / proteins
Therefore, when performing omics data analysis based on protein-protein interaction networks, those key node genes / proteins cannot be ignored.

Method used

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  • Protein-protein interaction network based gene set identification method
  • Protein-protein interaction network based gene set identification method
  • Protein-protein interaction network based gene set identification method

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Experimental program
Comparison scheme
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Embodiment

[0040] 1 method

[0041] 1.1 Protein-protein interaction data

[0042] Protein-protein interaction data come from STRING database 3,4 . The STRING database contains protein-protein physical and functional interaction data from multiple species. The inventors extracted human-specific protein-protein interaction data from it, and the combined socre of the interaction was at least 0.7. This standard not only ensures the high coverage of data, but also guarantees the high quality of data.

[0043] 1.2 Derivation of gene sets based on protein-protein interaction networks from THP1r2Mtb-induced

[0044] First, find the genes / proteins that directly interact with THP1r2Mtb-induced from the STING protein-protein interaction data, and name them as "node set", that is, the aforementioned "node set B". The genes / proteins in the node set are derived from protein-protein interaction data, and THP1r2Mtb-induced has no shared genes / proteins. Second, count the number of direct interactio...

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Abstract

The invention relates to a protein-protein interaction network based gene set identification method, and belongs to the technical field of genes. The identification method comprises the following steps: finding out genes / proteins in direct interaction with a 'set A' from a 'set B', and naming as a 'node set B'; counting the number of each gene / protein in the 'node set B' in direct interaction with the 'set A', and naming as a dimensionality 'i'; calling out the interactive genes / proteins from the 'set A' through the 'node set B [i]' with different minimal dimensionalities 'i', and naming as a 'set A [i]'; counting the aggregate z-score of the 'set A [i]'; adopting the 'set A [i]' with the maximal aggregate z-score as the obtained gene set. The identification method can identify the gene sets more relevant to the biological processes, and is helpful for relevant researchers to carry out correlational research work.

Description

technical field [0001] The invention belongs to the field of gene technology, and in particular relates to a gene set identification method based on protein-protein interaction network. Background technique [0002] Dynamic changes in the transcriptome / proteome cause changes in cellular function. Genes / proteins do not function independently, but function through interactions with other proteins in a protein-protein interaction network. Therefore, omics data mining based on protein-protein interaction network can discover some new biological information. Based on this, if omics data can be analyzed with the aid of protein-protein interaction information, the analysis results will be more biologically relevant. [0003] At present, the interaction network analysis of significantly regulated genes / proteins mainly relies on the direct interaction information between these genes / proteins. However, the expression of multiple genes / proteins indicated that it may interact with a ...

Claims

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Application Information

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IPC IPC(8): G06F19/18
Inventor 吴康黄家颖范小勇
Owner SHANGHAI PUBLIC HEALTH CLINICAL CENT
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