Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-20457
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kaufmann, Moritz | - |
dc.contributor.author | Schüle, Martin | - |
dc.contributor.author | Smits, Theo | - |
dc.contributor.author | Pothier, Joël | - |
dc.date.accessioned | 2020-09-10T16:51:44Z | - |
dc.date.available | 2020-09-10T16:51:44Z | - |
dc.date.issued | 2020-09-02 | - |
dc.identifier.isbn | 978-3-030-58308-8 | de_CH |
dc.identifier.isbn | 978-3-030-58309-5 | de_CH |
dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/20457 | - |
dc.description.abstract | Multidrug resistant bacteria represent an increasing challenge for medicine. In bacteria, most antibiotic resistances are transmitted by plasmids. Therefore, it is important to study the spread of plasmids in detail in order to initiate possible countermeasures. The classification of plasmids can provide insights into the epidemiology and transmission of plasmid-mediated antibiotic resistance. The previous methods to classify plasmids are replicon typing and MOB typing. Both methods are time consuming and labor-intensive. Therefore, a new approach to plasmid typing was developed, which uses word embeddings and support vector machines (SVM) to simplify plasmid typing. Visualizing the word embeddings with t-distributed stochastic neighbor embedding (t-SNE) shows that the word embeddings finds distinct structure in the plasmid sequences. The SVM assigned the plasmids in the testing dataset with an average accuracy of 85.9% to the correct MOB type. | de_CH |
dc.language.iso | en | de_CH |
dc.publisher | Springer | de_CH |
dc.relation.ispartofseries | Lecture Notes in Computer Science | de_CH |
dc.rights | Licence according to publishing contract | de_CH |
dc.subject | Word embedding | de_CH |
dc.subject | Support vector machine | de_CH |
dc.subject | Plasmid typing | de_CH |
dc.subject | Multidrug resistance | de_CH |
dc.subject | Antibiotic resistance | de_CH |
dc.subject.ddc | 572: Biochemie | de_CH |
dc.title | Typing plasmids with distributed sequence representation | de_CH |
dc.type | Konferenz: Paper | de_CH |
dcterms.type | Text | de_CH |
zhaw.departement | Life Sciences und Facility Management | de_CH |
zhaw.organisationalunit | Institut für Umwelt und Natürliche Ressourcen (IUNR) | de_CH |
zhaw.organisationalunit | Institut für Computational Life Sciences (ICLS) | de_CH |
zhaw.publisher.place | Cham | de_CH |
dc.identifier.doi | 10.1007/978-3-030-58309-5_16 | de_CH |
dc.identifier.doi | 10.21256/zhaw-20457 | - |
zhaw.conference.details | 9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020 | de_CH |
zhaw.funding.eu | No | de_CH |
zhaw.originated.zhaw | Yes | de_CH |
zhaw.pages.end | 210 | de_CH |
zhaw.pages.start | 200 | de_CH |
zhaw.parentwork.editor | Schilling, Frank-Peter | - |
zhaw.parentwork.editor | Stadelmann, Thilo | - |
zhaw.publication.status | acceptedVersion | de_CH |
zhaw.series.number | 12294 | de_CH |
zhaw.publication.review | Peer review (Publikation) | de_CH |
zhaw.title.proceedings | Artificial Neural Networks in Pattern Recognition | de_CH |
zhaw.funding.snf | 189340 | de_CH |
zhaw.webfeed | Digital Environment & Sustainability | de_CH |
zhaw.webfeed | Umweltgenomik | de_CH |
zhaw.webfeed | Health Research Hub (LSFM) | de_CH |
zhaw.funding.zhaw | ChitinOMix – A multidisciplinary project to understand the effect of chitin soil amendment on the plant response, natural microbial community and the fate of human pathogenic bacteria | de_CH |
zhaw.author.additional | No | de_CH |
zhaw.display.portrait | Yes | de_CH |
Appears in collections: | Publikationen Life Sciences und Facility Management |
Files in This Item:
File | Description | Size | Format | |
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2020_Kaufmann-etal_Typing-plasmids-with-distributed-sequence-representation_ANNPR.pdf | Accepted Version | 562.41 kB | Adobe PDF | View/Open |
Show simple item record
Kaufmann, M., Schüle, M., Smits, T., & Pothier, J. (2020). Typing plasmids with distributed sequence representation [Conference paper]. In F.-P. Schilling & T. Stadelmann (Eds.), Artificial Neural Networks in Pattern Recognition (pp. 200–210). Springer. https://doi.org/10.1007/978-3-030-58309-5_16
Kaufmann, M. et al. (2020) ‘Typing plasmids with distributed sequence representation’, in F.-P. Schilling and T. Stadelmann (eds) Artificial Neural Networks in Pattern Recognition. Cham: Springer, pp. 200–210. Available at: https://doi.org/10.1007/978-3-030-58309-5_16.
M. Kaufmann, M. Schüle, T. Smits, and J. Pothier, “Typing plasmids with distributed sequence representation,” in Artificial Neural Networks in Pattern Recognition, Sep. 2020, pp. 200–210. doi: 10.1007/978-3-030-58309-5_16.
KAUFMANN, Moritz, Martin SCHÜLE, Theo SMITS und Joël POTHIER, 2020. Typing plasmids with distributed sequence representation. In: Frank-Peter SCHILLING und Thilo STADELMANN (Hrsg.), Artificial Neural Networks in Pattern Recognition. Conference paper. Cham: Springer. 2 September 2020. S. 200–210. ISBN 978-3-030-58308-8
Kaufmann, Moritz, Martin Schüle, Theo Smits, and Joël Pothier. 2020. “Typing Plasmids with Distributed Sequence Representation.” Conference paper. In Artificial Neural Networks in Pattern Recognition, edited by Frank-Peter Schilling and Thilo Stadelmann, 200–210. Cham: Springer. https://doi.org/10.1007/978-3-030-58309-5_16.
Kaufmann, Moritz, et al. “Typing Plasmids with Distributed Sequence Representation.” Artificial Neural Networks in Pattern Recognition, edited by Frank-Peter Schilling and Thilo Stadelmann, Springer, 2020, pp. 200–10, https://doi.org/10.1007/978-3-030-58309-5_16.
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