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Center for Integrative Bioinformatics Vienna
Max F. Perutz Laboratories
Dr. Bohr Gasse 9
A-1030 Vienna, Austria

Welcome to Shortest Triplet Clustering

Introduction:

We propose a new distance-based clustering method, triplet clustering algorithm (STC), to reconstruct phylogenies. The main idea is the introduction of a natural definition of so-called k-representative sets. Based on k-representative sets, shortest triplets are reconstructed and serve as building blocks for the STC algorithm to agglomerate sequences for tree reconstruction in O(n^2) time for n sequences. Simulations with 500, 1000 and 5000 sequences data sets show that STC gives better topological accuracy than other methods tested.

Reference:

The method is described in detail in the following article:
  • Le Sy Vinh and Arndt von Haeseler, Shortest Triplet Clustering: Reconstructing Large Phylogenies, BMC-Bioinformatics.6:92. 2005.

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Data:


Printable version of: http://www.cibiv.at/software/stc/index.html

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