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Bioinformatics (Oxford, England)
|
August 22, 2009
ShotgunFunctionalizeR: an R-package for functional comparison of metagenomes
Erik Kristiansson, Philip Hugenholtz, Daniel Dalevi
Nature Communications
|
November 6, 2022
Economic interests cloud hazard reductions in the European regulation of substances of very high concern
Jessica Coria, Erik Kristiansson, Mikael Gustavsson
BMC Genomics
|
April 23, 2017
HirBin: high-resolution identification of differentially abundant functions in metagenomes
Tobias Österlund, Viktor Jonsson, Erik Kristiansson
Mbio
|
June 17, 2026
Reply to Bonomo and Hujer, "Enhancing clinical utility of AI-based antimicrobial resistance models: a perspective"
Juan S Inda-Díaz, Erik Kristiansson
Gigascience
|
September 10, 2015
Tentacle: distributed quantification of genes in metagenomes
Fredrik Boulund, Anders Sjögren, Erik Kristiansson
Future Microbiology
|
October 10, 2025
Data limitations hinder the development of AI-based decision support for the treatment of antibiotic-resistant bacteria
Anna Johnning, Styrbjörn Käll, Erik Kristiansson
BMC Genomics
|
January 27, 2016
Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics
Viktor Jonsson, Tobias Österlund, Olle Nerman, et al.
The Journal of Antimicrobial Chemotherapy
|
February 13, 2019
CMY-1/MOX-family AmpC β-lactamases MOX-1, MOX-2 and MOX-9 were mobilized independently from three Aeromonas species
Stefan Ebmeyer, Erik Kristiansson, D G Joakim Larsson
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
November 29, 2016
Variability in Metagenomic Count Data and Its Influence on the Identification of Differentially Abundant Genes
Viktor Jonsson, Tobias Österlund, Olle Nerman, et al.
Communications Biology
|
January 5, 2021
A framework for identifying the recent origins of mobile antibiotic resistance genes
Stefan Ebmeyer, Erik Kristiansson, D G Joakim Larsson
Page
of 15
Search research articles
Search
Showing results (1-10 of 142) with videos related to
Sort By:
Page
of 15
Bioinformatics (Oxford, England)
|
August 22, 2009
ShotgunFunctionalizeR: an R-package for functional comparison of metagenomes
Erik Kristiansson, Philip Hugenholtz, Daniel Dalevi
Nature Communications
|
November 6, 2022
Economic interests cloud hazard reductions in the European regulation of substances of very high concern
Jessica Coria, Erik Kristiansson, Mikael Gustavsson
BMC Genomics
|
April 23, 2017
HirBin: high-resolution identification of differentially abundant functions in metagenomes
Tobias Österlund, Viktor Jonsson, Erik Kristiansson
Mbio
|
June 17, 2026
Reply to Bonomo and Hujer, "Enhancing clinical utility of AI-based antimicrobial resistance models: a perspective"
Juan S Inda-Díaz, Erik Kristiansson
Gigascience
|
September 10, 2015
Tentacle: distributed quantification of genes in metagenomes
Fredrik Boulund, Anders Sjögren, Erik Kristiansson
Future Microbiology
|
October 10, 2025
Data limitations hinder the development of AI-based decision support for the treatment of antibiotic-resistant bacteria
Anna Johnning, Styrbjörn Käll, Erik Kristiansson
BMC Genomics
|
January 27, 2016
Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics
Viktor Jonsson, Tobias Österlund, Olle Nerman, et al.
The Journal of Antimicrobial Chemotherapy
|
February 13, 2019
CMY-1/MOX-family AmpC β-lactamases MOX-1, MOX-2 and MOX-9 were mobilized independently from three Aeromonas species
Stefan Ebmeyer, Erik Kristiansson, D G Joakim Larsson
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
November 29, 2016
Variability in Metagenomic Count Data and Its Influence on the Identification of Differentially Abundant Genes
Viktor Jonsson, Tobias Österlund, Olle Nerman, et al.
Communications Biology
|
January 5, 2021
A framework for identifying the recent origins of mobile antibiotic resistance genes
Stefan Ebmeyer, Erik Kristiansson, D G Joakim Larsson
Page
of 15