Evaluating deterministic motif significance measures in protein databases.

ABSTRACT:

Background

Assessing the outcome of motif mining algorithms is an essential task, as the number of reported motifs can be very large. Significance measures play a central role in automatically ranking those motifs, and therefore alleviating the analysis work. Spotting the most interesting and relevant motifs is then dependent on the choice of the right measures. The combined use of several measures may provide more robust results. However caution has to be taken in order to avoid spurious evaluations.

Results

From the set of conducted experiments, it was verified that several of the selected significance measures show a very similar behavior in a wide range of situations therefore providing redundant information. Some measures have proved to be more appropriate to rank highl

SUBMITTER: Ferreira PG 

PROVIDER: S-EPMC2254621 | biostudies-literature | 2007 Dec

REPOSITORIES: biostudies-literature