Unweighted Pair Group Method with Arithmetic Mean (UPGMA) is one of the most popular distance-based methods to reconstruct an equidistant phylogenetic tree from a distance matrix computed alignment sequences. Since we use trees as gene for phylogenomic analyses under multi-species coalescent model and since input each in genome estimated via maximum likelihood estimators, it important conduct r...

Distance-based methods such as UPGMA (Unweighted Pair Group Method with Arithmetic Mean) continue to play a significant role in phylogenetic research. We use polyhedral combinatorics to analyze the natural subdivision of the positive orthant induced by classifying the input vectors according to tree topologies returned by the algorithm. The partition lattice informs the study of UPGMA trees. We...

This investigation was aimed to compare the inference of antelope phylogenies resulting from the 16S rRNA, cytochrome-b (cyt-b) and d-loop segments of mitochondrial DNA using three different computational models including Bayesian (BA), maximum parsimony (MP) and unweighted pair group method with arithmetic mean (UPGMA). The respective nucleotide sequences of three Oryx species (Oryx leucoryx, ...

Department of Computer Science, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu City 30013, Taiwan Department of Computer Science and Information Engineering, Chang Gung University, No. 259, Sanmin Rd., Guishan Township, Taoyuan City 33302, Taiwan Department of Computer Science and Communication Engineering, Providence University, No. 200, Sec. 7, Taiwan Boulevard, Sha...

Motivation: UPGMA (average-linkage clustering) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. UPGMA however, is a complete-linkage method, in the sense that all edges between data points are needed in memory. Due to this prohibitive memory requirement UPGMA is not scalable for very large datasets. Results: We present novel memory-co...

A formula is given for a flexible combinatorial clustering strategy, having UPGMA and ISS as special cases. When numerical clustering methods are used to investigate the structure of taxonomic groups, it is common practice to try several methods, having different clustering intensities. For example, one might use single linkage (weak), UPGMA (medium), and complete linkage (strong) (Sneath and S...

MOTIVATION UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. APPLICATION We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any pr...

Methods Pattern analysis of a chorological dataset, consisting of the occurrences of 3041 vascular plant species in each of the 50 km 9 50 km UTM cells of a grid covering Iberia and the Balearic Islands, was based on cluster analysis (unweighted pair-group method using arithmetic averages; UPGMA) and parsimony analysis of endemicity (PAE). The Jaccard similarity index was used in the UPGMA, and...