Background: A phylogenetic tree which describes the evolutionary relationships among
various species from a common ancestor is a fundamental concept in evolutionary biology. In recent
years, a number of models of this tree structure have been proposed, mainly based on constructing a
similar hierarchical structure or grouping together descendents with common ancestors.
Objective: We use vertices in an acyclic graph to represent different organisms, and seek those
relatively important vertices of almost same descendents by tracing generations back of a set of vertices.
Method: We propose an algorithm for grouping based on previously theoretical analysis, which can
alleviate the negative effects of incorrect initial central vertices and noisy frontier vertices by two
strategies used in group merging step in our algorithm.
Results: The computational results in Clostridia show that our algorithm illustrates the data features
better compared with the traditional hierarchy clustering method.