Bacterial Identifier: Accelerating Bacterial Genome Detection

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Nejezchlebová, Julie
Rychlík, Ivan
Schwarzerová, Jana

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Mark

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Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

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Abstract

Bacterial identification is crucial for effectively monitoring and controlling the spread of infectious diseases. In addressing this critical need, our study introduces an engineered application designed to expedite the analysis of bacterial sequencing data, thus providing a streamlined method for species identification. The Bacterial Identifier underwent thorough testing using a significant dataset obtained from the Veterinary Research Institute. Central to the app's functionality is the integration of three essential tools. Implemented through a cohesive bash script, these tools are seamlessly combined to ensure optimal performance and accuracy in bacterial identification. Furthermore, to enhance user experience, a userfriendly interface was developed using Python 3, facilitating intuitive navigation and efficient utilization of the application's capabilities.

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Proceedings I of the 30st Conference STUDENT EEICT 2024: General papers. s. 97-100. ISBN 978-80-214-6231-1
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_1.pdf

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Peer-reviewed

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en

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