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整合性在的方法来分析人类疾病中微RNA介导反应

Meghna Agrawal¹, Ashutosh Mani¹

¹Department of Biotechnology, Motilal Nehru Institute of Technology Allahabad, Prayagraj, India.

The journal of gene medicine

|August 28, 2024

概括

本综述解释了如何使用in silico方法分析人类疾病中的微RNA (miRNA) 和信使RNA (mRNA) 相互作用. 它详细介绍了工作流程和统计解决方案,以了解miRNA介导的基因调节和识别疾病生物标志物.

科学领域:

基因组学和生物信息学
分子生物学分子生物学
计算生物学计算生物学

背景情况:

高通量测序技术使人类疾病的OMIC数据生成成为可能.
理解复杂的转录网络需要整合微RNA (miRNA) 和信使RNA (mRNA) 数据.
miRNAs是人类疾病中关键的基因调节者.

研究的目的:

提供一个概念工作流来分析使用in silico方法在人类疾病中的miRNA介导反应.
讨论miRNA目标基因预测和网络分析的优点,局限性和统计解决方案.
提出一种综合性方法来分析多源数据以识别疾病分子特征.

主要方法:

在miRNA和mRNA表达数据的in silico分析.
miRNA-目标基因预测方法.
对miRnome-targetome相互作用进行丰富和网络分析.
开发一个整合性工作流程来分析高通量数据.

主要成果:

介绍了分析人类疾病中miRNA介导反应的通用工作流.
讨论了各种in silico分析方法的优点和局限性.
突出了克服分析局限性的统计技术.
提出了一种整合性工作流程,用于分析生物网络的结构组件.

结论:

提出的方法和工作流程有助于分析多源数据,以识别人类疾病的分子特征.
本综述增强了对人类生物过程中miRNA介导的基因调节事件的理解.
这些发现有助于研究人员应用现有的方法来有效地分析miRNA介导的疾病反应.

关键词:

基因监管网络基因监管网络基因组丰富分析分析在的整合性分析.这是一个微型RNA.预测分析预测分析

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