Highlights
- •Considerable human resource is dedicated to interpreting electropherograms in forensic biology facilities.
- •Artificial neural networks are a powerful tool that can be used to recognise patterns and classify data.
- •We demonstrate an artificial neural network trained to ‘read’ electropherograms and show it generalised to unseen profiles.
- •There is potential for the use of artificial neural networks to be extended to reading complex, mixed electrophoretic data.
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
us about the underlying DNA sequences and what is purely an artefact of the DNA profiling
process. A technique that lends itself well to such a task of classification in the
face of vast amounts of data is the use of artificial neural networks. These networks,
inspired by the workings of the human brain, have been increasingly successful in
analysing large datasets, performing medical diagnoses, identifying handwriting, playing
games, or recognising images. In this work we demonstrate the use of an artificial
neural network which we train to ‘read’ electropherograms and show that it can generalise
to unseen profiles.
Keywords
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Article info
Publication history
Published online: July 29, 2016
Accepted:
July 26,
2016
Received in revised form:
July 24,
2016
Received:
June 5,
2016
Identification
Copyright
© 2016 Elsevier Ireland Ltd. All rights reserved.
