Journal of Jilin University Science Edition ›› 2022, Vol. 60 ›› Issue (2): 458-466.

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Exploringing for ALS Susceptibility Genes Based on Data Integration Strategy

YANG Yiyan1,  SONG Jiayue2,  ZENG Linlin2,  FU Xueqi2   

  1. 1. School Hospital of Jilin University,  Changchun 130012,  China; 
    2. Edmond Fischer Signal Transduction Laboratory,  School of Life Sciences,  Jilin University,  Changchun 130012,  China
  • Received:2021-05-18 Online:2022-03-26 Published:2022-03-26

Abstract: Amyotrophic lateral sclerosis (ALS) was a neurodegenerative disease characterized by motor neuron apoptosis. There was no effective treatment and drug at present. The discovery of new related genes or target genes played an important role in the study of pathogenesis and clinical treatment of ALS,  and provided a new direction and target for clinical prevention,  diagnosis and treatment. We collected the data information of ALS related genes from the website database,   used a variety of pathogenic gene prediction tool software for bioinformatics analysis,  and predicted the pathogenic genes. After the integration of data information,   39 candidate genes were obtained. The results show that the candidate  genes  have a certain correlation with ALS.

Key words: amyotrophic lateral sclerosis (ALS), network database, susceptibitity gene, gene prediction tool

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