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Viktor Jonsson
Viktor Jonsson
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Untreated urban waste contaminates Indian river sediments with resistance genes to last resort antibiotics
NP Marathe, C Pal, SS Gaikwad, V Jonsson, E Kristiansson, DGJ Larsson
Water Research 124, 388-397, 2017
1362017
Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics
V Jonsson, T Österlund, O Nerman, E Kristiansson
BMC genomics 17 (1), 1-14, 2016
1222016
Comparison of normalization methods for the analysis of metagenomic gene abundance data
MB Pereira, M Wallroth, V Jonsson, E Kristiansson
BMC genomics 19 (1), 1-17, 2018
952018
Industrial wastewater treatment plant enriches antibiotic resistance genes and alters the structure of microbial communities
J Bengtsson-Palme, M Milakovic, H Švecová, M Ganjto, V Jonsson, ...
Water research 162, 437-445, 2019
762019
Tissue-specific transcriptional imprinting and heterogeneity in human innate lymphoid cells revealed by full-length single-cell RNA-sequencing
L Mazzurana, P Czarnewski, V Jonsson, L Wigge, M Ringnér, TC Williams, ...
Cell research 31 (5), 554-568, 2021
682021
Strategies to improve usability and preserve accuracy in biological sequence databases
J Bengtsson‐Palme, F Boulund, R Edström, A Feizi, A Johnning, ...
Proteomics 16 (18), 2454-2460, 2016
492016
Magnetic phase diagram of K2Cr8O16 clarified by high-pressure muon spin spectroscopy
OK Forslund, D Andreica, Y Sassa, H Nozaki, I Umegaki, E Nocerino, ...
Scientific reports 9 (1), 1-10, 2019
192019
Computational and statistical considerations in the analysis of metagenomic data
F Boulund, MB Pereira, V Jonsson, E Kristiansson
Metagenomics, 81-102, 2018
192018
Variability in metagenomic count data and its influence on the identification of differentially abundant genes
V Jonsson, T Österlund, O Nerman, E Kristiansson
Journal of Computational Biology 24 (4), 311-326, 2017
162017
Modelling of zero-inflation improves inference of metagenomic gene count data
V Jonsson, T Österlund, O Nerman, E Kristiansson
Statistical methods in medical research 28 (12), 3712-3728, 2019
132019
HirBin: high-resolution identification of differentially abundant functions in metagenomes
T Österlund, V Jonsson, E Kristiansson
BMC genomics 18 (1), 1-11, 2017
132017
What is the role of the environment in the emergence of novel antibiotic resistance genes? A modeling approach
J Bengtsson-Palme, V Jonsson, S Heß
Environmental Science & Technology 55 (23), 15734-15743, 2021
102021
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data
S Magesh, V Jonsson, J Bengtsson-Palme
Metabarcoding and Metagenomics 3, e36236, 2019
52019
Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572
S Magesh, V Jonsson, J Bengtsson-Palme
Link, 0
5
Mitochondrial dysfunction in adult midbrain dopamine neurons triggers an early immune response
R Filograna, S Lee, K Tiklova, M Mennuni, V Jonsson, M Ringnér, ...
PLoS Genetics 17 (9), e1009822, 2021
42021
Statistical analysis and modelling of gene count data in metagenomics
V Jonsson
Sweden: Göteborg, 2017
32017
Quantifying point-mutations in shotgun metagenomic data
S Magesh, V Jonsson, J Bengtsson-Palme
bioRxiv, 438572, 2018
12018
Cross-validation of correlation networks using modular structure
M Neuman, V Jonsson, J Calatayud, M Rosvall
Applied Network Science 7 (1), 75, 2022
2022
Statistical analysis and modelling of gene count data in metagenomics
J Viktor
2017
A hierarchical Bayesian model for gene ranking in in metagenomics based on differential abundance
V Jonsson
9th European Conference on Mathematical and Theoretical Biology, 2014
2014
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