| Autor: |
Gabriele Fici, Alessio Langiu, Giosuè Lo Bosco, Riccardo Rizzo |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
AIMS Medical Science, Vol 5, Iss 1, Pp 23-32 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
2375-1576 |
| DOI: |
10.3934/medsci.2018.1.23 |
| Popis: |
Bacteria classification has been deeply investigated with different tools for many purposes,such as early diagnosis, metagenomics, phylogenetics. Classification methods based on ribosomalDNA sequences are considered a reference in this area. We present a new classificatier for bacteriaspecies based on a dissimilarity measure of purely combinatorial nature. This measure is based onthe notion of Minimal Absent Words, a combinatorial definition that recently found applications inbioinformatics. We can therefore incorporate this measure into a probabilistic neural network in orderto classify bacteria species. Our approach is motivated by the fact that there is a vast literature on thecombinatorics of Minimal Absent Words in relation with the degree of repetitiveness of a sequence.We ran our experiments on a public dataset of Ribosomal RNA Sequences from the complex 16S. Ourapproach showed a very high score in the accuracy of the classification, proving hence that our methodis comparable with the standard tools available for the automatic classification of bacteria species. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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