Open AccessComparative and integrative analysis of RNA structural profiling data: current practices and emerging questions
Author(s) -
Choudhary Krishna,
Deng Fei,
Aviran Sharon
Publication year - 2017
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.1007/s40484-017-0093-6
Subject(s) - profiling (computer programming) , data science , pace , computer science , computational biology , nucleic acid structure , data mining , biology , rna , genetics , geodesy , gene , geography , operating system
Background 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. Results 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. Conclusions 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.