Format

Send to

Choose Destination
See comment in PubMed Commons below
Pak J Pharm Sci. 2014 Jul;27(4 Suppl):1001-4.

Dynamic matching algorithm for viral structure prediction.

Author information

1
School of Computer Science and Technology and Shandong Provincial Key Laboratory of Digital Media Technology, Shandong University of Finance and Economics, Jinan, China.
2
School of Computer Science and Technology and Shandong Provincial Key Laboratory of Software Engineering, Shandong University, Jinan, China.
3
School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China.

Abstract

Most viruses have RNA genomes, their biological functions are expressed more by folded architecture than by sequence. Among the various RNA structures, pseudoknots are the most typical. In general, RNA secondary structures prediction doesn't contain pseudoknots because of its difficulty in modeling. Here we present an algorithm of dynamic matching to predict RNA secondary structures with pseudoknots by combining the merits of comparative and thermodynamic approaches. We have tested and verified our algorithm on some viral RNA. Comparisons show that our algorithm and loop matching method has similar accuracy and time complexity, and are more sensitive than the maximum weighted matching method and Rivas algorithm. Among the four methods, our algorithm has the best prediction specificity. The results show that our algorithm is more reliable and efficient than the other methods.

PMID:
25016258
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Loading ...
    Support Center