Suppr超能文献

循环 microRNA 转运和调控:计算原理与实践。

Circulating microRNA trafficking and regulation: computational principles and practice.

机构信息

Systems Biology and Biomedical Informatics Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.

出版信息

Brief Bioinform. 2020 Jul 15;21(4):1313-1326. doi: 10.1093/bib/bbz079.

Abstract

Rapid advances in genomics discovery tools and a growing realization of microRNA's implication in intercellular communication have led to a proliferation of studies of circulating microRNA sorting and regulation across cells and different species. Although sometimes, reaching controversial scientific discoveries and conclusions, these studies have yielded new insights in the functional roles of circulating microRNA and a plethora of analytical methods and tools. Here, we consider this body of work in light of key computational principles underpinning discovery of circulating microRNAs in terms of their sorting and targeting, with the goal of providing practical guidance for applications that is focused on the design and analysis of circulating microRNAs and their context-dependent regulation. We survey a broad range of informatics methods and tools that are available to the researcher, discuss their key features, applications and various unsolved problems and close this review with prospects and broader implication of this field.

摘要

基因组学发现工具的快速发展和对 microRNA 在细胞间通讯中的作用的认识不断提高,导致了对循环 microRNA 分选和调节的研究在细胞和不同物种中的大量涌现。尽管有时会得出有争议的科学发现和结论,但这些研究为循环 microRNA 的功能作用以及大量分析方法和工具提供了新的见解。在这里,我们根据循环 microRNA 分选和靶向的关键计算原理,考虑这方面的工作,目的是为专注于循环 microRNA 及其与上下文相关的调节的设计和分析的应用提供实用的指导。我们调查了广泛的可用于研究人员的信息学方法和工具,讨论了它们的主要特点、应用以及各种未解决的问题,并在这篇综述的结尾展望了这个领域的前景和更广泛的影响。

相似文献

1
Circulating microRNA trafficking and regulation: computational principles and practice.
Brief Bioinform. 2020 Jul 15;21(4):1313-1326. doi: 10.1093/bib/bbz079.
2
The evolution of tumour phylogenetics: principles and practice.
Nat Rev Genet. 2017 Apr;18(4):213-229. doi: 10.1038/nrg.2016.170. Epub 2017 Feb 13.
5
Expanding the horizons of microRNA bioinformatics.
RNA. 2018 Aug;24(8):1005-1017. doi: 10.1261/rna.065565.118. Epub 2018 Jun 5.
6
Computational Prediction of microRNA Targets.
Adv Exp Med Biol. 2015;887:231-52. doi: 10.1007/978-3-319-22380-3_12.
7
Mechanistic Computational Models of MicroRNA-Mediated Signaling Networks in Human Diseases.
Int J Mol Sci. 2019 Jan 19;20(2):421. doi: 10.3390/ijms20020421.
9
Understanding principles of miRNA target recognition and function through integrated biological and bioinformatics approaches.
Wiley Interdiscip Rev RNA. 2014 May-Jun;5(3):361-79. doi: 10.1002/wrna.1217. Epub 2014 Jan 23.
10
Experimental Validation of MicroRNA Targets: Analysis of MicroRNA Targets Through Western Blotting.
Methods Mol Biol. 2019;1970:341-353. doi: 10.1007/978-1-4939-9207-2_19.

引用本文的文献

2
A bioinformatics analysis of the target role of miRNA-431-5p on KLK6 in colorectal cancer.
Hereditas. 2025 Mar 28;162(1):46. doi: 10.1186/s41065-025-00395-7.
3
Diabetic Cardiomyopathy: Role of Cell Death, Exosomes, Fibrosis and Epicardial Adipose Tissue.
Int J Mol Sci. 2024 Aug 31;25(17):9481. doi: 10.3390/ijms25179481.
4
MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications.
Int J Mol Sci. 2024 Mar 31;25(7):3914. doi: 10.3390/ijms25073914.
5
Advances in Research Related to MicroRNA for Diabetic Retinopathy.
J Diabetes Res. 2024 Feb 12;2024:8520489. doi: 10.1155/2024/8520489. eCollection 2024.

本文引用的文献

1
MicroRNA expression, targeting, release dynamics and early-warning biomarkers in acute cardiotoxicity induced by triptolide in rats.
Biomed Pharmacother. 2019 Mar;111:1467-1477. doi: 10.1016/j.biopha.2018.12.109. Epub 2019 Jan 31.
3
Human Absorbable MicroRNA Prediction based on an Ensemble Manifold Ranking Model.
Proceedings (IEEE Int Conf Bioinformatics Biomed). 2015 Nov;2015:295-300. doi: 10.1109/BIBM.2015.7359697. Epub 2015 Dec 17.
5
Genome-scale MicroRNA target prediction through clustering with Dirichlet process mixture model.
BMC Genomics. 2018 Sep 24;19(Suppl 7):658. doi: 10.1186/s12864-018-5029-7.
6
miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts.
PLoS Comput Biol. 2018 Jul 13;14(7):e1006185. doi: 10.1371/journal.pcbi.1006185. eCollection 2018 Jul.
7
Trends in the development of miRNA bioinformatics tools.
Brief Bioinform. 2019 Sep 27;20(5):1836-1852. doi: 10.1093/bib/bby054.
8
A systematic approach to RNA-associated motif discovery.
BMC Genomics. 2018 Feb 14;19(1):146. doi: 10.1186/s12864-018-4528-x.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验