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微小RNA与癌症——探索之旅开始!

MicroRNAs and cancer-the search begins!

作者信息

Oulas Anastasis, Reczko Martin, Poirazi Panayiota

机构信息

Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Greece.

出版信息

IEEE Trans Inf Technol Biomed. 2009 Jan;13(1):67-77. doi: 10.1109/TITB.2008.2007086.

Abstract

For almost three decades, cancer was thought to result from changes in the structure and/or expression of protein coding genes. The discovery of thousands of genes that produce noncoding RNA (ncRNA) transcripts in the past few years suggested that the molecular biology of cancer is much more complex. MicroRNAs (miRNAs), an important group of ncRNAs, have recently been associated with tumorigenesis by acting either as tumor suppressors or oncogenes. Experimental prediction of miRNA genes is a slow process, because of the difficulties of cloning ncRNAs. Complementary to experimental approaches, a number of computational tools trained to recognize features of the biogenesis of miRNAs have significantly aided in the prediction of new miRNA candidates. By narrowing down the search space, computational approaches provide valuable clues as to which are the dominant features that characterize these regulatory units and which genes are their most likely targets. Moreover, through the use of high-throughput expression profiling methods, many molecular signatures of miRNA deregulation in human tumors have emerged. In this review, we present an overview of existing computational methods for identifying miRNA genes and assessing their expression levels, and analyze the contribution of such tools toward illuminating the role of miRNAs in cancer.

摘要

近三十年来,癌症一直被认为是由蛋白质编码基因的结构和/或表达变化所致。在过去几年中,数千种产生非编码RNA(ncRNA)转录本的基因被发现,这表明癌症的分子生物学要复杂得多。微小RNA(miRNA)是ncRNA的一个重要类别,最近被认为通过充当肿瘤抑制因子或癌基因参与肿瘤发生。由于克隆ncRNA存在困难,miRNA基因的实验预测是一个缓慢的过程。与实验方法相辅相成的是,一些经过训练以识别miRNA生物合成特征的计算工具极大地助力了新miRNA候选物的预测。通过缩小搜索空间,计算方法为哪些是表征这些调控单元的主要特征以及哪些基因是其最可能的靶标提供了有价值的线索。此外,通过使用高通量表达谱分析方法,人类肿瘤中miRNA失调的许多分子特征已显现出来。在本综述中,我们概述了用于识别miRNA基因并评估其表达水平的现有计算方法,并分析了此类工具对于阐明miRNA在癌症中的作用所做的贡献。

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