Publication detail

Clustering of Klebsiella Strains Based on Variability in Sequencing Data

BARTOŇ, V. NYKRÝNOVÁ, M. BEZDÍČEK, M. LENGEROVÁ, M. ŠKUTKOVÁ, H.

Original Title

Clustering of Klebsiella Strains Based on Variability in Sequencing Data

English Title

Clustering of Klebsiella Strains Based on Variability in Sequencing Data

Type

conference paper

Language

en

Original Abstract

Genotyping is a method necessary to distinguish between strains of bacteria. Using whole sequences for analysis is a computational demanding and time-consuming approach. We establish a workflow to convert sequences to a numerical signal representing the variability of sequences. After segmentation and using only parts of the signals, they have still enough information to form a topologically according to the clustering structure.

English abstract

Genotyping is a method necessary to distinguish between strains of bacteria. Using whole sequences for analysis is a computational demanding and time-consuming approach. We establish a workflow to convert sequences to a numerical signal representing the variability of sequences. After segmentation and using only parts of the signals, they have still enough information to form a topologically according to the clustering structure.

Keywords

Genotyping; Klebsiella pneumoniae; Variability signal; Numerical processing;

Released

13.04.2019

ISBN

978-3-030-17934-2

Book

Bioinformatics and Biomedical Engineering. IWBBIO 2019.

Edition number

11466

Pages from

189

Pages to

199

Pages count

11

BibTex


@inproceedings{BUT156910,
  author="Vojtěch {Bartoň} and Markéta {Nykrýnová} and Matěj {Bezdíček} and Martina {Lengerová} and Helena {Škutková}",
  title="Clustering of Klebsiella Strains Based on Variability in Sequencing Data",
  annote="Genotyping is a method necessary to distinguish between strains of bacteria. Using whole sequences for analysis is a computational demanding and time-consuming approach. We establish a workflow to convert sequences to a numerical signal representing the variability of sequences. After segmentation and using only parts of the signals, they have still enough information to form a topologically according to the clustering structure.",
  booktitle="Bioinformatics and Biomedical Engineering. IWBBIO 2019.",
  chapter="156910",
  doi="10.1007/978-3-030-17935-9_18",
  howpublished="print",
  year="2019",
  month="april",
  pages="189--199",
  type="conference paper"
}