A review on methods for predicting miRNA–mRNA regulatory modules

IF 1.5 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Madhumita Madhumita, Sushmita Paul
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引用次数: 4

Abstract

Abstract Identification of complex interactions between miRNAs and mRNAs in a regulatory network helps better understand the underlying biological processes. Previously, identification of these interactions was based on sequence-based predicted target binding information. With the advancement in high-throughput omics technologies, miRNA and mRNA expression for the same set of samples are available. This helps develop more efficient and flexible approaches that work by integrating miRNA and mRNA expression profiles with target binding information. Since these integrative approaches of miRNA–mRNA regulatory modules (MRMs) detection is sufficiently able to capture the minute biological details, 26 such algorithms/methods/tools for MRMs identification are comprehensively reviewed in this article. The study covers the significant features underlying every method. Therefore, the methods are classified into eight groups based on mathematical approaches to understand their working and suitability for one’s study. An algorithm could be selected based on the available information with the users and the biological question under investigation.
miRNA-mRNA调控模块预测方法综述
摘要在调控网络中识别miRNA和mRNA之间的复杂相互作用有助于更好地理解潜在的生物学过程。以前,这些相互作用的鉴定是基于基于序列的预测靶标结合信息。随着高通量组学技术的进步,同一组样品的miRNA和mRNA表达是可用的。这有助于开发更有效和灵活的方法,通过整合miRNA和mRNA表达谱与靶结合信息来发挥作用。由于这些miRNA-mRNA调节模块(MRM)检测的综合方法足以捕捉微小的生物学细节,本文对26种用于MRM识别的算法/方法/工具进行了全面综述。这项研究涵盖了每种方法背后的重要特征。因此,根据数学方法将这些方法分为八组,以了解它们的有效性和适用性。可以根据用户的可用信息和正在调查的生物学问题来选择算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Integrative Bioinformatics
Journal of Integrative Bioinformatics Medicine-Medicine (all)
CiteScore
3.10
自引率
5.30%
发文量
27
审稿时长
12 weeks
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