计算推断的包括转录后调控的调节心脏衰老模型

G. Politano, F. Logrand, M. Brancaccio, S. Carlo
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引用次数: 1

摘要

在大多数发达国家,心血管疾病是导致死亡的主要原因之一,而老龄化是心血管疾病发展的主要危险因素。在不同的因素中,mirna已被确定为心脏病理发展的相关参与者,它们影响基因网络的能力表明它们是潜在的治疗靶点或诊断标志物。本文提出了一项计算研究,该研究将数据融合技术与网络分析理论相结合,以确定能够表示参与心脏衰老过程的关键基因和mirna之间关系的调节模型。该模型已通过广泛的文献分析得到验证,能够将94%的鉴定基因和mirna与心脏衰老相关的研究联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A computationally inferred regulatory heart aging model including post-transcriptional regulations
Cardiovascular diseases are one of the leading causes of death in most developed countries and aging is a dominant risk factor for their development. Among the different factors, miRNAs have been identified as relevant players in the development of cardiac pathologies and their ability to influence gene networks suggests them as potential therapeutic targets or diagnostic markers. This paper presents a computational study that applies data fusion techniques coupled with network analysis theory to identify a regulatory model able to represent the relationship between key genes and miRNAs involved in cardiac senescence processes. The model has been validated through an extensive literature analysis that was able to connect 94% of the identified genes and miRNAs with cardiac senescence related studies.
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