SEK: sparsity exploiting k-mer-based estimation of bacterial community composition.

Chatterjee, S., Koslicki, D., Dong, S. et al. (8 more authors) (2014) SEK: sparsity exploiting k-mer-based estimation of bacterial community composition. Bioinformatics, 30 (17). pp. 2423-2431. ISSN 1367-4803

Abstract

Metadata

Authors/Creators:
  • Chatterjee, S.
  • Koslicki, D.
  • Dong, S.
  • Innocenti, N.
  • Cheng, L.
  • Lan, Y.
  • Vehkaperä, M.
  • Skoglund, M.
  • Rasmussen, L.K.
  • Aurell, E.
  • Corander, J.
Copyright, Publisher and Additional Information: © The Author 2014. Published by Oxford University Press. This is an author produced version of a paper subsequently published in Bioinformatics. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Algorithms; Bacteria; High-Throughput Nucleotide Sequencing; Metagenomics; Models, Statistical; RNA, Ribosomal, 16S; Sequence Analysis, DNA
Dates:
  • Published: 1 September 2014
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 15 Feb 2016 12:41
Last Modified: 29 Mar 2018 02:22
Published Version: http://dx.doi.org/10.1093/bioinformatics/btu320
Status: Published
Publisher: Oxford University Press
Refereed: Yes
Identification Number: https://doi.org/10.1093/bioinformatics/btu320
Related URLs:

Share / Export

Statistics