<div class="csl-bib-body">
<div class="csl-entry">Lamurias, A., Tibo, A., Hose, K., Albertsen, M., & Nielsen, T. D. (2023). Graph Neural Networks for Metagenomic Binning. In <i>The 2023 ICML Workshop on Computational Biology. Accepted Submissions</i>. 40th International Conference on Machine Learning (ICML 2023), Honolulu, United States of America (the). ICML compbio workshop. https://doi.org/10.34726/5406</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/193202
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dc.identifier.uri
https://doi.org/10.34726/5406
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dc.description.abstract
Most methods for metagenomic binning relysolely on the local properties of the individual contigs. Because of this, these techniques are unable to take advantage of the connections between contigs as established by the assembly graph. In this paper, we explore Graph Neural Networks (GNNs) to leverage the assembly graph when learning contig representations for metagenomic binning. We applied four different types of GNN architectures, comparing their results on real and synthetic datasets, demonstrating encouraging results and, therefore, a promising research direction to pursue and explore.
en
dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.subject
Graph Neural Networks
en
dc.subject
Metagenomic Binning
en
dc.subject
Assembly Graph
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dc.subject
Explore
en
dc.subject
Microbial communities
en
dc.subject
Environment
en
dc.subject
DNA sequencing technologies
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dc.subject
Deep Learning
en
dc.subject
real-world datasets
en
dc.subject
Wastewater Treatment Plant (WWTP)
en
dc.subject
Data Science
en
dc.subject
Bioinformatics
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dc.title
Graph Neural Networks for Metagenomic Binning
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
en
dc.rights.license
Creative Commons Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International
de
dc.identifier.doi
10.34726/5406
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dc.contributor.affiliation
Aalborg University, Denmark
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dc.contributor.affiliation
Aalborg University, Denmark
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dc.contributor.affiliation
Aalborg University, Denmark
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dc.contributor.affiliation
Aalborg University, Denmark
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dc.rights.holder
Copyright 2023 by the author(s)
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
The 2023 ICML Workshop on Computational Biology. Accepted Submissions
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tuw.peerreviewed
true
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tuw.relation.publisher
ICML compbio workshop
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tuw.researchTopic.id
I1
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tuw.researchTopic.name
Logic and Computation
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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dc.identifier.libraryid
AC17204937
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dc.description.numberOfPages
7
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tuw.author.orcid
0000-0001-7025-8099
-
tuw.author.orcid
0000-0002-4823-6341
-
dc.rights.identifier
CC BY-NC-ND 4.0
en
dc.rights.identifier
CC BY-NC-ND 4.0
de
tuw.event.name
40th International Conference on Machine Learning (ICML 2023)
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dc.description.sponsorshipexternal
Villum Fonden
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dc.relation.grantnoexternal
34299
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tuw.event.startdate
23-07-2023
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tuw.event.enddate
29-07-2023
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Honolulu
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tuw.event.country
US
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tuw.event.presenter
Nielsen, Thomas Dyhre
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tuw.event.track
Multi Track
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
80
-
wb.sciencebranch.value
20
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item.mimetype
application/pdf
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item.openairetype
conference paper
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item.cerifentitytype
Publications
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item.grantfulltext
open
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item.languageiso639-1
en
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.openaccessfulltext
Open Access
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item.fulltext
with Fulltext
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crisitem.author.dept
Aalborg University
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crisitem.author.dept
Aalborg University
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
