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lncRNA数据库:新兴工具的比较评估

Databases for lncRNAs: a comparative evaluation of emerging tools.

作者信息

Fritah Sabrina, Niclou Simone P, Azuaje Francisco

机构信息

NorLux Neuro-Oncology Laboratory, Department of Oncology, Centre de Recherche Public de la Santé (CRP-Santé), Luxembourg L-1526, Luxembourg.

NorLux Neuro-Oncology Laboratory, Department of Oncology, Centre de Recherche Public de la Santé (CRP-Santé), Luxembourg L-1526, Luxembourg

出版信息

RNA. 2014 Nov;20(11):1655-65. doi: 10.1261/rna.044040.113.

Abstract

The vast majority of the human transcriptome does not code for proteins. Advances in transcriptome arrays and deep sequencing are giving rise to a fast accumulation of large data sets, particularly of long noncoding RNAs (lncRNAs). Although it is clear that individual lncRNAs may play important and diverse biological roles, there is a large gap between the number of existing lncRNAs and their known relation to molecular/cellular function. This and related information have recently been gathered in several databases dedicated to lncRNA research. Here, we review the content of general and more specialized databases on lncRNAs. We evaluate these resources in terms of the quality of annotations, the reporting of validated or predicted molecular associations, and their integration with other resources and computational analysis tools. We illustrate our findings using known and novel cancer-related lncRNAs. Finally, we discuss limitations and highlight potential future directions for these databases to help delineating functions associated with lncRNAs.

摘要

人类转录组的绝大多数并不编码蛋白质。转录组阵列和深度测序技术的进步导致大量数据集迅速积累,尤其是长链非编码RNA(lncRNA)的数据集。尽管很明显单个lncRNA可能发挥重要且多样的生物学作用,但现有lncRNA的数量与其已知的分子/细胞功能之间仍存在很大差距。最近,这些信息以及相关信息已被收集到几个专门用于lncRNA研究的数据库中。在此,我们综述了lncRNA通用及更专业数据库的内容。我们从注释质量、已验证或预测的分子关联报告以及它们与其他资源和计算分析工具的整合方面对这些资源进行评估。我们用已知及新发现的与癌症相关的lncRNA来说明我们的发现。最后,我们讨论这些数据库的局限性,并强调其未来潜在的发展方向,以帮助阐明与lncRNA相关的功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e4f/4201818/0a4f5858ba93/1655f01.jpg

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