Tapinos, A. and Robertson, D. L. (2017) De Novo Assembly of Nucleotide Sequences in a Compressed Feature Space. In: 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Manchester, UK, 23-25 Aug 2017, ISBN 9781467389884 (doi: 10.1109/CIBCB.2017.8058556)
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Abstract
Sequencing technologies allow for an in-depth analysis of biological species but the size of the generated datasets introduce a number of analytical challenges. Recently, we demonstrated the application of numerical sequence representations and data transformations for the alignment of short reads to a reference genome. Here, we expand out approach for de novo assembly of short reads. Our results demonstrate that highly compressed data can encapsulate the signal suffi- ciently to accurately assemble reads to big contigs or complete genomes.
Item Type: | Conference Proceedings |
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Additional Information: | We thank Shaun Kandathil, Bede Constandinides and Samaneh Kouchaki for valuable recommendations, data sharing and for assistance with coding. Funding: this work has been supported by the BBSRC [BB/M001121/1], and the VIROGENESIS project which receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 634650. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Robertson, Professor David |
Authors: | Tapinos, A., and Robertson, D. L. |
College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research |
ISBN: | 9781467389884 |
Published Online: | 05 October 2017 |
Copyright Holders: | Copyright © 2017 IEEE |
First Published: | First published in 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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