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Genome Biology and Evolution
|
May 17, 2011
Mutation rate distribution inferred from coincident SNPs and coincident substitutions
Philip L F Johnson, Ines Hellmann
Molecular Ecology
|
August 21, 2015
Detecting recent selective sweeps while controlling for mutation rate and background selection
Christian D Huber, Michael DeGiorgio, Ines Hellmann, et al.
Molecular Biology and Evolution
|
August 28, 2014
Keeping it local: evidence for positive selection in Swedish Arabidopsis thaliana
Christian D Huber, Magnus Nordborg, Joachim Hermisson, et al.
Bioinformatics (Oxford, England)
|
August 20, 2009
The effects of probe binding affinity differences on gene expression measurements and how to deal with them
Michael Dannemann, Anna Lorenc, Ines Hellmann, et al.
Gigascience
|
May 31, 2018
zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs
Swati Parekh, Christoph Ziegenhain, Beate Vieth, et al.
Briefings in Functional Genomics
|
March 27, 2018
Quantitative single-cell transcriptomics
Christoph Ziegenhain, Beate Vieth, Swati Parekh, et al.
Genome Research
|
January 14, 2010
Population genetic inference from genomic sequence variation
John E Pool, Ines Hellmann, Jeffrey D Jensen, et al.
Scientific Reports
|
May 10, 2016
The impact of amplification on differential expression analyses by RNA-seq
Swati Parekh, Christoph Ziegenhain, Beate Vieth, et al.
Bioinformatics (Oxford, England)
|
October 17, 2017
powsimR: power analysis for bulk and single cell RNA-seq experiments
Beate Vieth, Christoph Ziegenhain, Swati Parekh, et al.
Nature Communications
|
October 13, 2019
A systematic evaluation of single cell RNA-seq analysis pipelines
Beate Vieth, Swati Parekh, Christoph Ziegenhain, et al.
Page
of 5
Search research articles
Search
Showing results (1-10 of 44) with videos related to
Sort By:
Page
of 5
Genome Biology and Evolution
|
May 17, 2011
Mutation rate distribution inferred from coincident SNPs and coincident substitutions
Philip L F Johnson, Ines Hellmann
Molecular Ecology
|
August 21, 2015
Detecting recent selective sweeps while controlling for mutation rate and background selection
Christian D Huber, Michael DeGiorgio, Ines Hellmann, et al.
Molecular Biology and Evolution
|
August 28, 2014
Keeping it local: evidence for positive selection in Swedish Arabidopsis thaliana
Christian D Huber, Magnus Nordborg, Joachim Hermisson, et al.
Bioinformatics (Oxford, England)
|
August 20, 2009
The effects of probe binding affinity differences on gene expression measurements and how to deal with them
Michael Dannemann, Anna Lorenc, Ines Hellmann, et al.
Gigascience
|
May 31, 2018
zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs
Swati Parekh, Christoph Ziegenhain, Beate Vieth, et al.
Briefings in Functional Genomics
|
March 27, 2018
Quantitative single-cell transcriptomics
Christoph Ziegenhain, Beate Vieth, Swati Parekh, et al.
Genome Research
|
January 14, 2010
Population genetic inference from genomic sequence variation
John E Pool, Ines Hellmann, Jeffrey D Jensen, et al.
Scientific Reports
|
May 10, 2016
The impact of amplification on differential expression analyses by RNA-seq
Swati Parekh, Christoph Ziegenhain, Beate Vieth, et al.
Bioinformatics (Oxford, England)
|
October 17, 2017
powsimR: power analysis for bulk and single cell RNA-seq experiments
Beate Vieth, Christoph Ziegenhain, Swati Parekh, et al.
Nature Communications
|
October 13, 2019
A systematic evaluation of single cell RNA-seq analysis pipelines
Beate Vieth, Swati Parekh, Christoph Ziegenhain, et al.
Page
of 5