Motivation: Recent results related to horizontal gene transfer suggest that phylogenetic reconstruction cannot be determined conclusively from sequence data, resulting in a shift from approaches based on polymorphism information in DNA or protein sequence to studies aimed at understanding the evolution of complete biological processes. The increasing amount of available information on metabolic pathways for several species makes it of greater relevance to understand the similarities and differences among such pathways. These similarities can then be used to infer phylogenetic trees not based exclusively in sequence data, therefore avoiding the previously mentioned problems.#R##N##R##N#Results: In this article, we present a method to assess the structural similarity of metabolic pathways for several organisms. Our algorithms work by using one of the three possible enzyme similarity measures (hierarchical, information content, gene ontology), and one of the two clustering methods (neighbor-joining, unweighted pair group method with arithmetic mean), to produce a phylogenetic tree both in Newick and graphic format. The web server implementing our algorithms is optimized to answer queries in linear time.#R##N##R##N#Availability: The software is available for free public use on a web server, at the address http://www.jaist.ac.jp/~clemente/cgi-bin/phylo.pl. It is available on demand in source code form for research use to educational institutions, non-profit research institutes, government research laboratories and individuals, for non-exclusive use, without the right of the licensee to further redistribute the source code.#R##N##R##N#Contact:valiente@lsi.upc.edu; clemente@jaist.ac.jp
['Jose C. Clemente', 'Kenji Satou', 'Gabriel Valiente']
Phylogenetic reconstruction from non-genomic data