Constructing accurate contact maps for hydroxyl-radical-cleavage-based high-throughput RNA structure inference

Jinkyu Kim, Hanjoo Kim, Hyeyoung Min, Sungroh Yoon

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


For rapid ribonucleic acid (RNA) tertiary structure prediction, innovative methods have been proposed that exploit hydroxyl radical cleavage agents in a high-throughput manner. In such techniques, it is critical to determine accurately which residue a specific cleavage agent interacts with, since this information directly reveals the residueresidue interaction points needed for structure inference. Due to lack of effective automated methods, the process of locating contact points has been mostly done manually, becoming a bottleneck of the whole procedure. To address this problem, we propose a novel computational method to determine residueresidue interaction points from 2-D electrophoresis profiles. This method combines the deconvolution method for signal detection and statistical learning techniques for filtering noise, thus boosting specificity and sensitivity in harmony. According to our experiments with over 2000 actual gel profiles, the proposed technique exhibited 56.44%-90.50% higher performance than traditional methods in terms of the accuracy of reproducing manual contact maps measured by the F-measure, a widely used evaluation metric. We expect that adopting the proposed technique will significantly accelerate RNA tertiary structure inference, allowing researchers to explore more structures in given time.

Original languageEnglish
Article number5705566
Pages (from-to)1347-1355
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Issue number5
Publication statusPublished - 2011 May
Externally publishedYes

Bibliographical note

Funding Information:
Manuscript received September 27, 2010; revised December 15, 2010, January 19, 2011; accepted January 21, 2011. Date of publication January 31, 2011; date of current version April 20, 2011. This work was supported in part by the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology under Grant 2010-0000407 and Grant 2010-0000631. Asterisk indicates corresponding author.


  • Biological signal processing
  • deconvolution
  • pattern recognition
  • ribonucleic acid (RNA)
  • structural bioinformatics

ASJC Scopus subject areas

  • Biomedical Engineering


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