An artificial neural network system to identify alleles in reference electropherograms

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dc.contributor.authorTaylor, Duncan A
dc.contributor.authorHarrison, A
dc.contributor.authorPowers, David Martin
dc.date.accessioned2017-07-25T05:04:26Z
dc.date.available2017-07-25T05:04:26Z
dc.date.issued2017-07-06
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 policyen
dc.description.abstractElectropherograms 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.citationTaylor, D., Harrison, A., & Powers, D. (2017). An artificial Neural Network system to identify alleles in reference electropherograms. Forensic Science International: Genetics.en
dc.identifier.doihttps://doi.org/10.1016/j.fsigen.2017.07.002en
dc.identifier.issn1872-4973
dc.identifier.urihttp://hdl.handle.net/2328/37358
dc.language.isoen
dc.oaire.license.condition.licenseCC-BY-NC-ND
dc.publisherElsevieren
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.holderElsevieren
dc.subjectElectropherogramen
dc.subjectGel readingen
dc.subjectArtificial neural networken
dc.subjectAllele detectionen
dc.titleAn artificial neural network system to identify alleles in reference electropherogramsen
dc.typeArticleen
local.contributor.authorOrcidLookupTaylor, Duncan A: https://orcid.org/0000-0003-0633-7424
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