Improved phylogenetic motif detection using parsimony

Usman Roshan, Dennis R. Livesay, David La

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


We have recently demonstrated (La et al, Proteins, 58:2005) that sequence fragments approximating the overall familial phylogeny, called phylogenetic motifs (PMs), represent a promising protein functional site prediction strategy. Previous results across a structurally and functionally diverse dataset indicate that phylogenetic motifs correspond to a wide variety of known functional characteristics. Phylogenetic motifs are detected using a sliding window algorithm that compares neighbor joining trees on the complete alignment to those on the sequence fragments. In this investigation we identify PMs using heuristic maximum parsimony trees. We show that when using parsimony the functional site prediction accuracy of PMs improves substantially, particularly on divergent datasets. We also show that the new PMs found using parsimony are not necessarily conserved in sequence, and, therefore, would not be detected by traditional motif (information content-based) approaches.

Original languageEnglish (US)
Title of host publicationProceedings - BIBE 2005
Subtitle of host publication5th IEEE Symposium on Bioinformatics and Bioengineering
Number of pages8
StatePublished - 2005
EventBIBE 2005: 5th IEEE Symposium on Bioinformatics and Bioengineering - Minneapolis, MN, United States
Duration: Oct 19 2005Oct 21 2005

Publication series

NameProceedings - BIBE 2005: 5th IEEE Symposium on Bioinformatics and Bioengineering


OtherBIBE 2005: 5th IEEE Symposium on Bioinformatics and Bioengineering
Country/TerritoryUnited States
CityMinneapolis, MN

All Science Journal Classification (ASJC) codes

  • General Engineering


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