Home > Search Results: Talanin, Nikita
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Gene identification in nanopore squiggles
 Talanin, Nikita ; Nykrýnová, Markéta (referee) ; Bartoň, Vojtěch (advisor)
Nanopore sequencing is a new and rapidly developing technology that allows for the direct sequencing of single-stranded DNA and RNA in real-time. The result of the sequencing is the so-called squiggle, which is a time series of current intensities as nucleotides pass through the nanopore. Identifying genes in these squiggles is a crucial step for the utilization of this data in genomic studies. This bachelor's thesis focuses on the development and testing of a method for automatic gene identification in squiggles from nanopore sequencing. The aim was to create a system capable of quickly and accurately identifying genes in squiggles, thereby supporting further analysis and interpretation of nanopore sequencing data. The method utilizes Convolutional Neural Networks (CNN), which have been successfully used in many other areas of bioinformatics. A large dataset of squiggles, labeled according to the gene they represent, was used to train the model. The results show that the system can identify genes in squiggles with a certain level of accuracy and can be an effective tool for nanopore sequencing data analysis
Detailed record
Gene identification in nanopore squiggles
 Talanin, Nikita ; Nykrýnová, Markéta (referee) ; Bartoň, Vojtěch (advisor)
Nanopore sequencing is a new and rapidly developing technology that allows for the direct sequencing of single-stranded DNA and RNA in real-time. The result of the sequencing is the so-called squiggle, which is a time series of current intensities as nucleotides pass through the nanopore. Identifying genes in these squiggles is a crucial step for the utilization of this data in genomic studies. This bachelor's thesis focuses on the development and testing of a method for automatic gene identification in squiggles from nanopore sequencing. The aim was to create a system capable of quickly and accurately identifying genes in squiggles, thereby supporting further analysis and interpretation of nanopore sequencing data. The method utilizes Convolutional Neural Networks (CNN), which have been successfully used in many other areas of bioinformatics. A large dataset of squiggles, labeled according to the gene they represent, was used to train the model. The results show that the system can identify genes in squiggles with a certain level of accuracy and can be an effective tool for nanopore sequencing data analysis
Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English