Method for identifying long-chain non-coding ribonucleic acid-transcription factor-gene regulation motif

A transcription factor and ribonucleic acid technology, applied in genomics, instrumentation, proteomics, etc., to achieve the effects of accurate data, accurate results, and novel solutions

Active Publication Date: 2020-05-01
XIAN UNIV OF TECH
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Problems solved by technology

However, few studies have explored the effect of lncRNAs on the regulation of TF-gene interactions through lncRNA-mediated miRNA involvement in cancer

Method used

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  • Method for identifying long-chain non-coding ribonucleic acid-transcription factor-gene regulation motif

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Embodiment Construction

[0031] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0032] A method for identifying lncRNA-TF-gene regulatory motifs based on a multiple linear regression model, the method comprising the following steps:

[0033] Step 1, get gene expression data:

[0034] From XENA (XENA is a database developed by the University of California, Santa Cruz, named XENA. The URL of the database is https: / / xenabrowser.net / ) to download various cancer-related genes and their numbers, diagnostic basic data, and cancer genome map Provides transcriptome sequencing data in 33 common cancer tissues and para-cancerous tissues. These samples in The Cancer Genome Atlas can be used to analyze expression profiles. The original RNA-seq (RNA-seq transcriptome sequencing technology) provided by The Cancer Genome ) sequencing data can be used to calculate the expression levels of lncRNA (lncRNA means long-chain non-coding RNA), ...

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Abstract

The invention discloses a method for identifying a long-chain non-coding ribonucleic acid-transcription factor-gene regulation motif. The method comprises the following steps: step 1, acquiring gene expression data; step 2, filtering the gene expression data; step 3, acquiring a regulation relationship between biomolecules; step 4, acquiring long-chain non-coding RNAs with high expression and lowexpression; 5, designing a multiple linear regression model; and step 6, result processing. The method disclosed by the invention can be used for identifying the lncRNA-TF-gene regulation motif in complex diseases; and reliable lncRNA, TF and gene expression data and reliable TF-gene regulation relationship data are obtained by adopting strict filtering conditions, so a result output by a subsequent multiple linear regression model is more reliable and credible, and system errors are reduced.

Description

technical field [0001] The invention belongs to the technical field of identifying lncRNA-TF-gene regulatory motifs, and in particular relates to an effective method for identifying lncRNA-TF-gene regulatory motifs based on a multiple linear regression model. Background technique [0002] At present, there are still many major diseases threatening people's health, even life-threatening. Cancer is undoubtedly a complex disease that has received the most attention among many major diseases. Globally, about 15% of deaths are caused by cancer. The diagnosis and treatment of cancer still face great challenges. In January 2019, the National Cancer Center of my country published the "2019 China Latest Cancer Report" in the "Chinese Journal of Oncology". According to the report, an average of 7.5 people are diagnosed with cancer every minute in China. As my country's population aging process continues to accelerate, the year-on-year cancer rate continues to rise, and the number ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/00
CPCG16B20/00
Inventor 李爱民刘雅君刘光明费蓉周红芳黑新宏王磊赵中明
Owner XIAN UNIV OF TECH
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