Suppr超能文献

参与癌症的微小RNA的计算鉴定

Computational identification of miRNAs involved in cancer.

作者信息

Oulas Anastasis, Karathanasis Nestoras, Poirazi Panayiota

机构信息

Institute for Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Heraklion, Crete, Greece.

出版信息

Methods Mol Biol. 2011;676:23-41. doi: 10.1007/978-1-60761-863-8_2.

Abstract

Changes in the structure and/or the expression of protein-coding genes were thought to be the major cause of cancer for many decades. However, the recent discovery of non-coding RNA (ncRNA) transcripts suggests that the molecular biology of cancer is far more complex. MicroRNAs (miRNAs) are key players of the family of ncRNAs and they have been under extensive investigation because of their involvement in carcinogenesis, often taking up roles of tumor suppressors or oncogenes. Owing to the slow nature of experimental identification of miRNA genes, computational procedures have been applied as a valuable complement to cloning. Numerous computational tools, implemented to recognize the characteristic features of miRNA biogenesis, have resulted in the prediction of multiple novel miRNA genes. Computational approaches provide valuable clues as to which are the dominant features that characterize these regulatory units and furthermore act by narrowing down the search space making experimental verification faster and significantly cheaper. Moreover, in combination with large-scale, high-throughput methods, such as deep sequencing and tilling arrays, computational methods have aided in the discovery of putative molecular signatures of miRNA deregulation in human tumors. This chapter focuses on existing computational methods for identifying miRNA genes, provides an overview of the methodology undertaken by these tools, and underlies their contribution toward unraveling the role of miRNAs in cancer.

摘要

几十年来,人们一直认为蛋白质编码基因的结构和/或表达变化是癌症的主要原因。然而,非编码RNA(ncRNA)转录本的最新发现表明,癌症的分子生物学要复杂得多。微小RNA(miRNA)是ncRNA家族的关键成员,由于它们参与致癌过程,常常发挥肿瘤抑制因子或癌基因的作用,因此受到了广泛研究。由于miRNA基因的实验鉴定过程缓慢,计算程序已被用作克隆的重要补充。为识别miRNA生物合成的特征而开发的众多计算工具,已预测出多个新的miRNA基因。计算方法为表征这些调控单元的主要特征提供了有价值的线索,并且通过缩小搜索空间发挥作用,使实验验证更快且成本显著降低。此外,与深度测序和tiling阵列等大规模高通量方法相结合,计算方法有助于发现人类肿瘤中miRNA失调的推定分子特征。本章重点介绍用于识别miRNA基因的现有计算方法,概述这些工具所采用的方法,并强调它们对阐明miRNA在癌症中的作用所做的贡献。

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