Please use this identifier to cite or link to this item: doi:10.22028/D291-44181
Title: In silico read normalization using set multi-cover optimization
Author(s): Durai, Dilip
Schulz, Marcel H.
Language: English
Title: Bioinformatics
Volume: 34
Issue: 19
Pages: 3273-3280
Publisher/Platform: Oxford Univ. Press
Year of Publication: 2018
DDC notations: 004 Computer science, internet
Publikation type: Journal Article
Abstract: De Bruijn graphs are a common assembly data structure for sequencing datasets. But with the advances in sequencing technologies, assembling high coverage datasets has become a computational challenge. Read normalization, which removes redundancy in datasets, is widely applied to reduce resource requirements. Current normalization algorithms, though efficient, provide no guarantee to preserve important k-mers that form connections between regions in the graph.
DOI of the first publication: 10.1093/bioinformatics/bty307
URL of the first publication: https://academic.oup.com/bioinformatics/article/34/19/3273/4975418
Link to this record: urn:nbn:de:bsz:291--ds-441812
hdl:20.500.11880/39514
http://dx.doi.org/10.22028/D291-44181
ISSN: 1367-4811
1367-4803
Date of registration: 28-Jan-2025
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Keiner Professur zugeordnet
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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