Analysis of Optical Mapping Data with Neural Network

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248618" target="_blank" >RIV/61989100:27240/21:10248618 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-84910-8_26" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-84910-8_26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-84910-8_26" target="_blank" >10.1007/978-3-030-84910-8_26</a>

Result language
angličtina
Original language name
Analysis of Optical Mapping Data with Neural Network
Original language description
Optical Mapping is a method of DNA sequencing, that can be used to detect large structural variations in genomes. To create these optical maps, a restriction enzyme is mixed with DNA where the enzyme binds to DNA creating labels called restriction sites. These restriction sites and can be captured by fluorescent microscope with a camera. One of the tools that can capture these images is Bionano Genomics Saphyr mapping instrument. Their system produces high-resolution images of DNA molecules with restriction sites and their software detects them. Molecules in these images are visualized by gray lines with restrictions sites appearing brighter. Some of these molecules have very low brightness and with static noise around them, they are almost indistinguishable from the background. This work proposes GPU accelerated method for molecule detection. A neural network was used for molecule segmentation from the image and the dataset for the network was created from the results of Bionano Genomics tools. This detection method can be used as a substitute for restriction map detection in the Bionano Genomics processing pipeline or as a tool that can highlight the regions of interest in the raw optical maps images. (C) 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Czech name
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Czech description
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Project
<a href="/en/project/NU20-06-00269" target="_blank" >NU20-06-00269: Utility of cellular profiles and proteomics of synovial fluid and periprosthetic tissues for clinical decision making in knee osteoarthritis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Networks and Systems. Volume 312
ISBN
978-3-030-84909-2
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
243-252
Publisher name
Springer
Place of publication
Cham
Event location
Tchaj-čung
Event date
Sep 1, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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