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A survey on computational approaches to identifying disease biomarkers based on molecular networks

机译:基于分子网络的疾病生物标志物识别方法研究

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The disease biomarkers can help make accurate diagnosis and therefore give appropriate interventions. In the past years, the accumulation of various kinds of 'omics' data, e.g. genomics and transcriptomics, makes it possible to identify disease biomarkers in a more efficient way. In particular, the molecular networks that describe the functional relationships among molecules enable the identification of disease biomarkers from a systematic perspective. In this paper, we surveyed the recent progress on the computational approaches that have been developed to identify disease biomarkers based on molecular networks. In addition, we introduced the popular resources about human interactomes and regulatomes as well as human diseasomes, whose availability makes it possible to predict the disease biomarkers with the utility of networks. (C) 2014 Elsevier Ltd. All rights reserved.
机译:疾病生物标记物可以帮助进行准确的诊断,因此可以进行适当的干预。在过去的几年中,各种“组学”数据的积累,例如基因组学和转录组学使以更有效的方式鉴定疾病生物标记成为可能。特别地,描述分子间功能关系的分子网络使得能够从系统的角度鉴定疾病生物标志物。在本文中,我们调查了基于分子网络识别疾病生物标记物的计算方法的最新进展。此外,我们介绍了有关人类交互基因组和正常小器官以及人类疾病的流行资源,这些资源的可用性使人们可以利用网络来预测疾病生物标志物。 (C)2014 Elsevier Ltd.保留所有权利。

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