An artificial neural network system to identify alleles in reference electropherograms

dc.contributor.author Taylor, Duncan A
dc.contributor.author Harrison, A
dc.contributor.author Powers, David Martin
dc.date.accessioned 2017-07-25T05:04:26Z
dc.date.available 2017-07-25T05:04:26Z
dc.date.issued 2017-07-06
dc.description © 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (July 2017) in accordance with the publisher’s archiving policy en
dc.description.abstract Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells them about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. This process of interpreting the electropherograms can be time consuming and is prone to subjective differences between analysts. Recently it was demonstrated that artificial neural networks could be used to classify information within an electropherogram as allelic (i.e. representative of a DNA fragment present in the DNA extract) or as one of several different categories of artefactual fluorescence that arise as a result of generating an electropherogram. We extend that work here to demonstrate a series of algorithms and artificial neural networks that can be used to identify peaks on an electropherogram and classify them. We demonstrate the functioning of the system on several profiles and compare the results to a leading commercial DNA profile reading system. en
dc.identifier.citation Taylor, D., Harrison, A., & Powers, D. (2017). An artificial Neural Network system to identify alleles in reference electropherograms. Forensic Science International: Genetics. en
dc.identifier.doi https://doi.org/10.1016/j.fsigen.2017.07.002 en
dc.identifier.issn 1872-4973
dc.identifier.uri http://hdl.handle.net/2328/37358
dc.language.iso en
dc.oaire.license.condition.license CC-BY-NC-ND
dc.publisher Elsevier en
dc.rights © 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ en
dc.rights.holder Elsevier en
dc.subject Electropherogram en
dc.subject Gel reading en
dc.subject Artificial neural network en
dc.subject Allele detection en
dc.title An artificial neural network system to identify alleles in reference electropherograms en
dc.type Article en
local.contributor.authorOrcidLookup Taylor, Duncan A: https://orcid.org/0000-0003-0633-7424
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