Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions.
Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions.
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DOI：
10.1007/s40484-017-0093-6
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发表时间：
2017-03
期刊：
影响因子：
--
通讯作者：
Aviran S
中科院分区：
文献类型：
--
作者：
Choudhary K;Deng F;Aviran S
结构分析实验提供RNA结构的单核苷酸信息。化学的最新进展与高通量测序的应用相结合，使转录组规模和活细胞的结构分析成为可能，为RNA生物学创造了前所未有的机会。在这些实验进展的推动下，产生了具有不断增加的多样性和复杂性的大量数据，这给解释和分析这些数据带来了新的挑战。我们回顾了结构分析数据分析的现行做法，重点是比较和综合分析，以及突出新出现的问题。比较分析揭示了转录组的结构模式，并已成为最近的分析研究的一个组成部分。此外，剖析数据可以集成到传统的结构预测算法中，以提高预测精度。为了跟上实验发展的步伐，需要促进、加强和改进这种分析的方法。分析方法的平行进步将补充特征分析技术，并帮助它们充分发挥潜力。
Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transcriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.
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影响因子：
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作者：
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影响因子：
14.9
作者：
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