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  • 标题:Soft Topographic Maps for Clustering and Classifying Bacteria Using Housekeeping Genes
  • 本地全文:下载
  • 作者:Massimo La Rosa ; Riccardo Rizzo ; Alfonso Urso
  • 期刊名称:Advances in Artificial Neural Systems
  • 印刷版ISSN:1687-7594
  • 电子版ISSN:1687-7608
  • 出版年度:2011
  • 卷号:2011
  • DOI:10.1155/2011/617427
  • 出版社:Hindawi Publishing Corporation
  • 摘要: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.
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