Table of Contents
Advances in Artificial Neural Systems
Volume 2011, Article ID 617427, 8 pages
http://dx.doi.org/10.1155/2011/617427
Research Article

Soft Topographic Maps for Clustering and Classifying Bacteria Using Housekeeping Genes

ICAR-CNR, Consiglio Nazionale delle Ricerche, Viale delle Scienze, Ed.11, 90128 Palermo, Italy

Received 11 May 2011; Revised 13 July 2011; Accepted 26 July 2011

Academic Editor: Tomasz G. Smolinski

Copyright © 2011 Massimo La Rosa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The Self-Organizing Map (SOM) algorithm is widely used for building topographic maps of data represented in a vectorial space, but it does not operate with dissimilarity data. Soft Topographic Map (STM) algorithm is an extension of SOM to arbitrary distance measures, and it creates a map using a set of units, organized in a rectangular lattice, defining data neighbourhood relationships. In the last years, a new standard for identifying bacteria using genotypic information began to be developed. In this new approach, phylogenetic relationships of bacteria could be determined by comparing a stable part of the bacteria genetic code, the so-called “housekeeping genes.” The goal of this work is to build a topographic representation of bacteria clusters, by means of self-organizing maps, starting from genotypic features regarding housekeeping genes.