吉林大学学报(理学版) ›› 2022, Vol. 60 ›› Issue (2): 458-466.

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基于数据整合策略探究肌萎缩侧索硬化症易感基因

杨翊研1, 宋佳玥2, 曾琳琳2, 付学奇2   

  1. 1. 吉林大学 校医院, 长春130012; 
    2. 吉林大学 生命科学学院, Edmond Fischer细胞信号传导实验室, 长春130012
  • 收稿日期:2021-05-18 出版日期:2022-03-26 发布日期:2022-03-26
  • 通讯作者: 付学奇 E-mail:fxq@jlu.edu.cn

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

摘要: 肌萎缩侧索硬化症(ALS)是一种以运动神经元凋亡为特征的神经退行性疾病, 目前尚无有效的治疗方法和药物. 发现新的相关基因或靶点基因, 对研究ALS的发病机制及临床治疗具有重要作用, 为临床预防、 诊断和治疗提供新的方向和目标.     从网站数据库搜集ALS相关基因的数据信息, 通过多种致病基因预测工具软件进行生物信息学分析, 并预测致病基因. 整合数据信息后得到39个候选基因. 结果表明,   候选基因与ALS均有一定的相关性. 

关键词: 肌萎缩侧索硬化症, 网络数据库, 易感基因, 基因预测工具

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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