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基于集成流形排序模型的人类可吸收微小RNA预测

Human Absorbable MicroRNA Prediction based on an Ensemble Manifold Ranking Model.

作者信息

Shu Jiang, Chiang Kevin, Zhao Dongyu, Cui Juan

机构信息

Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States.

出版信息

Proceedings (IEEE Int Conf Bioinformatics Biomed). 2015 Nov;2015:295-300. doi: 10.1109/BIBM.2015.7359697. Epub 2015 Dec 17.

DOI:10.1109/BIBM.2015.7359697
PMID:30416843
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6223015/
Abstract

MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.

摘要

微小RNA是一类短链非编码RNA,能够调控超过半数的人类基因,并影响许多基本生物学过程。长期以来,人们一直认为微小RNA是内源性合成的,直到最近的发现表明人类可以从饮食来源中吸收外源性微小RNA。这一发现提出了一个具有挑战性的科学问题:哪些外源性微小RNA能够进入人体循环并可能在人体内发挥作用?在此,我们提出了一个精心设计的集成流形排序模型,用于从14种常见饮食物种中识别可被人体吸收的外源性微小RNA。具体而言,我们分析了4910种饮食微小RNA,这些微小RNA具有基于其序列和结构衍生出的1120个特征。总共选择了70个具有判别力的特征来表征人体内循环的微小RNA,并用于推断特定外源性微小RNA进入人体循环的可能性。最终,461种饮食微小RNA被鉴定为可转运的外源性微小RNA。为了评估我们集成模型的性能,我们通过一项喂食牛奶的研究对排名靠前的预测结果进行了验证。此外,来自两种病毒的26种微小RNA被预测为可转运的,并在两项外部实验中得到了验证。结果表明,这种数据驱动的计算模型在研究可转运微小RNA方面极具前景,同时绕过了复杂的作用机制细节。

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Dietary MicroRNA Database (DMD): An Archive Database and Analytic Tool for Food-Borne microRNAs.饮食微小RNA数据库(DMD):一个用于食源性微小RNA的存档数据库和分析工具。
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