罕见疾病中的拼接缺陷:转录组学和机器学习策略朝着基因诊断的方向发展
Robert Wang1,2, Ingo Helbig3,4,5,6, Andrew C Edmondson1,7
1Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Briefings in bioinformatics
|August 14, 2023
概括
调查遗传疾病需要更好地检测拼接变体. RNA测序和计算工具改善了这些引起疾病的变体的识别,帮助诊断罕见疾病.
科学领域:
- 遗传学 遗传学 是一个
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 影响前信使RNA拼接的基因组变异与众多罕见遗传疾病有关.
- 当前的遗传诊断和变异解释方法往往无法识别结合改变变异,导致诊断差距.
- 越来越需要先进的方法来检测和解释致病拼接变体,以改善患者护理和研究.
结论:
- 测序技术和预测建模方面的持续进展将加深我们对拼接监管的理解.
- 这些进展对于弥合诊断差距和改善罕见遗传疾病患者的治疗结果至关重要.
- 结合RNA测序和计算分析的综合方法对于精确的诊断和罕见遗传疾病的研究至关重要.
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