An Important Connection Between Network Motifs and Parsimony Models

  • Teresa M. Przytycka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3909)


We demonstrate an important connection between network motifs in certain biological networks and validity of evolutionary trees constructed using parsimony methods. Parsimony methods assume that taxa are described by a set of characters and infer phylogenetic trees by minimizing number of character changes required to explain observed character states. From the perspective of applicability of parsimony methods, it is important to assess whether the characters used to infer phylogeny are likely to provide a correct tree. We introduce a graph theoretical characterization that helps to select correct characters. Given a set of characters and a set of taxa, we construct a network called character overlap graph. We show that the character overlap graph for characters that are appropriate to use in parsimony methods is characterized by significant under-representation of subnetworks known as holes, and provide a mathematical validation for this observation. This characterization explains success in constructing evolutionary trees using parsimony method for some characters (e.g. protein domains) and lack of such success for other characters (e.g. introns). In the latter case, the understanding of mathematical obstacles to applying parsimony methods in a direct way has lead us to a new approach for dealing with inconsistent and/or noisy data. Namely, we introduce the concept of persistent characters which is similar but less restrictive than the well known concept of pairwise compatible characters. Application of this approach to introns produces the evolutionary tree consistent with the Coelomata hypothesis. In contrast, the direct application of a parsimony method, using introns as characters, produces a tree which is inconsistent with any of the two competing evolutionary hypotheses. Similarly, replacing persistence with pairwise compatibility does not lead to a correct tree. This indicates that the concept of persistence provides an important addition to the parsimony metohds.


Evolutionary Tree Parsimony Model Network Motif Chordal Graph Parsimony Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Teresa M. Przytycka
    • 1
  1. 1.National Center for Biotechnology Information, US National Library of MedicineNational Institutes of HealthBethesdaUSA

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