All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Signal processing based CNV detection in bacterial genomes

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132855" target="_blank" >RIV/00216305:26220/19:PU132855 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-030-17938-0_9" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-17938-0_9</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-17938-0_9" target="_blank" >10.1007/978-3-030-17938-0_9</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Signal processing based CNV detection in bacterial genomes

  • Original language description

    Copy number variation (CNV) plays important role in drug resistance in bacterial genomes. It is one of the prevalent forms of structural variations which leads to duplications or deletions of regions with varying size across the genome. So far, most studies were concerned with CNV in eukaryotic, mainly human, genomes. The traditional laboratory methods as microarray genome hybridization or genotyping methods are losing its effectiveness with the omnipotent increase of fully sequenced genomes. Methods for CNV detection are predominantly targeted at eukaryotic sequencing data and only a few of tools is available for CNV detection in prokaryotic genomes. In this paper, we propose the CNV detection algorithm derived from state-of-the-art methods for peaks detection in the signal processing domain. The modified method of GC normalization with higher resolution is also presented for the needs of the CNV detection. The performance of the algorithms are discussed and analyzed.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20602 - Medical laboratory technology (including laboratory samples analysis; diagnostic technologies) (Biomaterials to be 2.9 [physical characteristics of living material as related to medical implants, devices, sensors])

Result continuities

  • Project

    <a href="/en/project/GA17-01821S" target="_blank" >GA17-01821S: High throughput bacterial genome assembly and annotation techniques using genomic signal processing</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Bioinformatics and Biomedical Engineering. IWBBIO 2019.

  • ISBN

    978-3-030-17937-3

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    93-102

  • Publisher name

    Springer Verlag

  • Place of publication

    Granada, Spain

  • Event location

    Granada

  • Event date

    May 8, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article