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ŠKUTKOVÁ, H. VÍTEK, M. BEZDÍČEK, M. BRHELOVÁ, E. LENGEROVÁ, M.
Original Title
Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data
Type
journal article in Web of Science
Language
English
Original Abstract
Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis over conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Most current methods evaluate only the pairwise similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation; unfortunately, that approach significantly reduces the ability to distinguish between closely related samples. This study presents a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples. The proposed approach allows the accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.
Keywords
DNA fingerprintingautomated chip capillary electrophoresisgenotypingband matchinggel sample distortionpattern recognition
Authors
ŠKUTKOVÁ, H.; VÍTEK, M.; BEZDÍČEK, M.; BRHELOVÁ, E.; LENGEROVÁ, M.
Released
25. 1. 2019
Publisher
Elsevier
ISBN
2090-1232
Periodical
Journal of Advanced Research
Year of study
18
Number
State
Arab Republic of Egypt
Pages from
9
Pages to
Pages count
10
URL
http://www.sciencedirect.com/science/article/pii/S2090123219300050
BibTex
@article{BUT155605, author="Helena {Vítková} and Martin {Vítek} and Matěj {Bezdíček} and Eva {Brhelová} and Martina {Lengerová}", title="Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data", journal="Journal of Advanced Research", year="2019", volume="18", number="18", pages="9--18", doi="10.1016/j.jare.2019.01.005", issn="2090-1232", url="http://www.sciencedirect.com/science/article/pii/S2090123219300050" }