Iterated Loop Matching (ILM)

An Approach to the Prediction of RNA Secondary Structures with Pseudoknots

Jianhua Ruan and Weixiong Zhang
Department of Computer Science and Department of Genetics
Washington University in St. Louis, St. Louis, MO 63130, USA
email: {jruan,zhang}@cse.wustl.edu; (314)935-8788; Fax:(314)935-7302

Iterated loop matching (ILM) is an extended dynamic programming algorithm that is able to predict RNA secondary structures including pseudoknots. ILM can not only predict consensus structures for aligned homologous sequences, using combined thermodynamic and covariance scores, but can also be applied to individual sequences, using thermodynamic information alone.

The method is implemented in ANSI C and can be freely downloaded here (gzipped tar file). See the README file for details.

To learn more about the method, take a look at a preprint version of the paper describing the method (postscript, pdf).

Supplementary Materials

• Comparison of prediction accuracy of ILM and other methods
  • Sequences used in the experiments
  • On aligned sequences
  • On individual sequences
• Comparison of predicted and accepted structues
  • 5S rRNA (E. coli):  text
  • SRP RNA (Bac. subtilis):   text  graph
  • Human Telomerase RNA 5'-end:  text  graph
  • tmRNA (E.coli):  text graph
  • 16S rRNA (E.coli):  text
  • HIV-RT-1
  • TYMV
  • TMV-3'-end downstream 105nt
  • TMV-3'-end upstream 84nt
  • HDV genome RNA
  • HDV antigenome RNA
• CPU time and memory usage