Bacterial phenotype prediction based on methylation site profiles
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148965" target="_blank" >RIV/00216305:26220/23:PU148965 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10264900" target="_blank" >https://ieeexplore.ieee.org/document/10264900</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CIBCB56990.2023.10264900" target="_blank" >10.1109/CIBCB56990.2023.10264900</a>
Alternative languages
Result language
angličtina
Original language name
Bacterial phenotype prediction based on methylation site profiles
Original language description
Methylated site mapping in the DNA sequences plays a key role in understanding the physiology and pathology of cells and organisms. Thanks to third-generation DNA sequencers, these epigenetic modifications can be detected already when reading genetic information. Therefore, not only genotypic classification but also phenotypic specifications can be determined based on a single sequencing run. However, for phenotyping purposes, there is still a lack of effective standardized tools to design uniform classification schemes for different laboratories. Here, we present a simple tool for comparing DNA methylation site profiles, utilizing sequencing reads mapping to the reference genome similar to core genome analysis in bacterial genotyping. The proposed pipeline maps sequence reads with marked positions of methylated bases to a single representative reference. Thus the output consists of the uniformly aligned methylated site positions in a set of bacterial genomes. This allows for the evaluation of common methylated sites across all genomes, i.e. ,,core methylome”, as well as unique methylated sites in gene and intergenic regions. Thus, determining the sequence type can be further refined by predicting bacterial behaviour such as antibiotic resistance or virulence.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA23-05845S" target="_blank" >GA23-05845S: Real-time determination of infection threats from raw nanopore signals using machine learning techniques</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
ISBN
979-8-3503-1017-7
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
neuveden
Event location
Eindhoven
Event date
Aug 29, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001090563700005