Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions

Krishna Choudhary, Fei Deng, Sharon Aviran

Research output: Contribution to journalReview articlepeer-review

21 Scopus citations


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. [Figure not available: see fulltext.].

Original languageEnglish (US)
Pages (from-to)3-24
Number of pages22
JournalQuantitative Biology
Issue number1
StatePublished - Mar 1 2017


  • chemical structure probing
  • high-throughput sequencing
  • RNA secondary structure prediction
  • RNA structure profiling
  • SHAPE-Seq

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computer Science Applications
  • Modeling and Simulation
  • Applied Mathematics


Dive into the research topics of 'Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions'. Together they form a unique fingerprint.

Cite this