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Kasper D Hansen

Showing results (11-20 of 81) with videos related to

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BMC Bioinformatics|February 20, 2010
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experimentsJames H Bullard, Elizabeth Purdom, Kasper D Hansen, et al.
NAR Genomics and Bioinformatics|May 3, 2021
Human methylome variation across Infinium 450K data on the Gene Expression OmnibusSean K Maden, Reid F Thompson, Kasper D Hansen, et al.
Genome Research|July 17, 2025
Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networksPrashanthi Ravichandran, Princy Parsana, Rebecca Keener, et al.
BMC Genomics|March 15, 2019
Linear models enable powerful differential activity analysis in massively parallel reporter assaysLeslie Myint, Dimitrios G Avramopoulos, Loyal A Goff, et al.
Genome Research|October 15, 2016
Whole-genome analysis of the methylome and hydroxymethylome in normal and malignant lung and liverXin Li, Yun Liu, Tal Salz, et al.
Analytical Chemistry|February 22, 2017
Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based MetabolomicsLeslie Myint, Andre Kleensang, Liang Zhao, et al.
Nature Biotechnology|July 13, 2011
Sequencing technology does not eliminate biological variabilityKasper D Hansen, Zhijin Wu, Rafael A Irizarry, et al.
Nature Methods|November 3, 2014
Coverage recommendations for methylation analysis by whole-genome bisulfite sequencingMichael J Ziller, Kasper D Hansen, Alexander Meissner, et al.
Bioinformatics (Oxford, England)|May 7, 2016
Rail-dbGaP: analyzing dbGaP-protected data in the cloud with Amazon Elastic MapReduceAbhinav Nellore, Christopher Wilks, Kasper D Hansen, et al.
Scientific Reports|December 10, 2015
DNA methylation is stable during replication and cell cycle arrestAmy R Vandiver, Adrian Idrizi, Lindsay Rizzardi, et al.
Pageof 9

Showing results (11-20 of 81) with videos related to

Sort By:
Pageof 9
BMC Bioinformatics|February 20, 2010
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experimentsJames H Bullard, Elizabeth Purdom, Kasper D Hansen, et al.
NAR Genomics and Bioinformatics|May 3, 2021
Human methylome variation across Infinium 450K data on the Gene Expression OmnibusSean K Maden, Reid F Thompson, Kasper D Hansen, et al.
Genome Research|July 17, 2025
Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networksPrashanthi Ravichandran, Princy Parsana, Rebecca Keener, et al.
BMC Genomics|March 15, 2019
Linear models enable powerful differential activity analysis in massively parallel reporter assaysLeslie Myint, Dimitrios G Avramopoulos, Loyal A Goff, et al.
Genome Research|October 15, 2016
Whole-genome analysis of the methylome and hydroxymethylome in normal and malignant lung and liverXin Li, Yun Liu, Tal Salz, et al.
Analytical Chemistry|February 22, 2017
Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based MetabolomicsLeslie Myint, Andre Kleensang, Liang Zhao, et al.
Nature Biotechnology|July 13, 2011
Sequencing technology does not eliminate biological variabilityKasper D Hansen, Zhijin Wu, Rafael A Irizarry, et al.
Nature Methods|November 3, 2014
Coverage recommendations for methylation analysis by whole-genome bisulfite sequencingMichael J Ziller, Kasper D Hansen, Alexander Meissner, et al.
Bioinformatics (Oxford, England)|May 7, 2016
Rail-dbGaP: analyzing dbGaP-protected data in the cloud with Amazon Elastic MapReduceAbhinav Nellore, Christopher Wilks, Kasper D Hansen, et al.
Scientific Reports|December 10, 2015
DNA methylation is stable during replication and cell cycle arrestAmy R Vandiver, Adrian Idrizi, Lindsay Rizzardi, et al.
Pageof 9