Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur 342037, Rajasthan, India.
J Integr Bioinform. 2022 Apr 1;19(3). doi: 10.1515/jib-2020-0048. eCollection 2022 Sep 1.
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.
在调控网络中识别 miRNA 和 mRNAs 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，这些相互作用的识别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，同一组样本的 miRNA 和 mRNA 表达情况都有了。这有助于开发更有效和灵活的方法，这些方法通过将 miRNA 和 mRNA 表达谱与靶标结合信息进行整合来实现。由于 miRNA-mRNA 调控模块 (MRM) 检测的这些集成方法能够充分捕捉到微小的生物学细节，因此本文全面综述了 26 种用于识别 MRM 的算法/方法/工具。该研究涵盖了每种方法的重要特征。因此，根据数学方法将方法分为八组，以了解它们的工作原理和适用于研究的适用性。可以根据用户和研究中的生物学问题选择可用信息的算法。
