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Soft topographic maps for clustering and classifying bacteria using housekeeping genes

Articolo
Data di Pubblicazione:
2011
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.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Topographic map clustering housekeeping genes
Elenco autori:
LA ROSA, Massimo; Rizzo, Riccardo; Urso, Alfonso
Autori di Ateneo:
LA ROSA MASSIMO
RIZZO RICCARDO
URSO ALFONSO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/12988
Pubblicato in:
ADVANCES IN ARTIFICIAL NEURAL SYSTEMS
Journal
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