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首页> 外文期刊>IEEE/ACM transactions on computational biology and bioinformatics >RFCM3: Computational Method for Identification of miRNA-mRNA Regulatory Modules in Cervical Cancer
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RFCM3: Computational Method for Identification of miRNA-mRNA Regulatory Modules in Cervical Cancer

机译：RFCM3：宫颈癌中miRNA-mRNA调节模块的计算方法

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摘要

Cervical cancer is a leading severe malignancy throughout the world. Molecular processes and biomarkers leading to tumor progression in cervical cancer are either unknown or only partially understood. An increasing number of studies have shown that microRNAs play an important role in tumorigenesis so understanding the regulatory mechanism of miRNAs in gene-regulatory network will help elucidate the complex biological processes that occur during malignancy. Functional genomics data provides opportunities to study the aberrant microRNA-messenger RNA (miRNA-mRNA) interaction. Identification of miRNA-mRNA regulatory modules will aid deciphering aberrant transcriptional regulatory network in cervical cancer but is computationally challenging. In this regard, an algorithm, termed as relevant and functionally consistent miRNA-mRNA modules (RFCM3), is proposed. It integrates miRNA and mRNA expression data of cervical cancer for identification of potential miRNA-mRNA modules. It selects set of miRNA-mRNA modules by maximizing relation of mRNAs with miRNA and functional similarity between selected mRNAs. Later, using the knowledge of the miRNA-miRNA synergistic network different modules are fused and finally a set of modules are generated containing several miRNAs as well as mRNAs. This type of module explains the underlying biological pathways containing multiple miRNAs and mRNAs. The effectiveness of the proposed approach over other existing methods has been demonstrated on a miRNA and mRNA expression data of cervical cancer with respect to enrichment analyses and other standard metrices. The prognostic value of the genes in a module with respect to cervical cancer is also demonstrated. The approach was found to generate more robust, integrated, and functionally enriched miRNA-mRNA modules in cervical cancer.
机译：宫颈癌是全世界领先的严重恶性肿瘤。导致宫颈癌中肿瘤进展的分子方法和生物标志物是未知的或仅部分地理解。越来越多的研究表明，MicroRNA在肿瘤发生中发挥着重要作用，因此了解MiRNA在基因调节网络中的调节机制将有助于阐明恶性肿瘤期间发生的复杂生物过程。功能基因组学数据提供了研究异常Microrna-Messenger RNA（miRNA-mRNA）相互作用的机会。 miRNA-mRNA调节模块的鉴定将有助于在宫颈癌中解入异常转录调节网络，但正在计算挑战。在这方面，提出了一种称为相关和功能一致的miRNA-mRNA模块（RFCM3）的算法。它集成了宫颈癌的miRNA和mRNA表达数据以鉴定潜在的miRNA-mRNA模块。它通过最大化MRNA与所选MRNA之间的功能相似性的MRNA的关系选择一组miRNA-mRNA模块。后来，使用MiRNA-MiRNA协同网络的知识不同模块融合，最后产生一组模块，其中包含多个MiRNA以及MRNA。这种类型的模块解释了含有多个miRNA和MRNA的底层生物途径。已经对宫颈癌的miRNA和mRNA表达数据进行了富集分析和其他标准额度，证明了提出的方法对其他现有方法的有效性。还证明了模块中基因的预后价值，相对于宫颈癌。发现该方法在宫颈癌中产生更强大，集成和功能富集的miRNA-mRNA模块。

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