Using deep learning for gene detection and classification in raw nanopore signals
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144361" target="_blank" >RIV/00216305:26220/22:PU144361 - isvavai.cz</a>
Alternative codes found
RIV/65269705:_____/22:00076376
Result on the web
<a href="https://www.frontiersin.org/articles/10.3389/fmicb.2022.942179/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fmicb.2022.942179/full</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3389/fmicb.2022.942179" target="_blank" >10.3389/fmicb.2022.942179</a>
Alternative languages
Result language
angličtina
Original language name
Using deep learning for gene detection and classification in raw nanopore signals
Original language description
Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals—squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analyzed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Microbiology
ISSN
1664-302X
e-ISSN
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Volume of the periodical
13
Issue of the periodical within the volume
1
Country of publishing house
CH - SWITZERLAND
Number of pages
11
Pages from-to
1-11
UT code for WoS article
000862142800001
EID of the result in the Scopus database
2-s2.0-85139009357