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Oliver Stegle

Showing results (1-10 of 181) with videos related to

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Nature Methods|September 14, 2023
Principles and challenges of modeling temporal and spatial omics dataBritta Velten, Oliver Stegle
Genome Biology|February 26, 2016
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expressionBarbara Rakitsch, Oliver Stegle
Genome Biology|May 13, 2020
Effects of the COVID-19 pandemic on life scientistsJan O Korbel, Oliver Stegle
Genome Biology|February 2, 2022
MUON: multimodal omics analysis frameworkDanila Bredikhin, Ilia Kats, Oliver Stegle
Nature Communications|June 26, 2015
A random forest approach to capture genetic effects in the presence of population structureJohannes Stephan, Oliver Stegle, Andreas Beyer
Science (New York, N.Y.)|October 7, 2017
Single-cell epigenomics: Recording the past and predicting the futureGavin Kelsey, Oliver Stegle, Wolf Reik
Nature Methods|March 20, 2018
SpatialDE: identification of spatially variable genesValentine Svensson, Sarah A Teichmann, Oliver Stegle
Genome Biology|December 15, 2019
Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype referenceYuanhua Huang, Davis J McCarthy, Oliver Stegle
Bioinformatics (Oxford, England)|June 30, 2016
GeneCodeq: quality score compression and improved genotyping using a Bayesian frameworkDaniel L Greenfield, Oliver Stegle, Alban Rrustemi
Plos Computational Biology|January 14, 2012
Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studiesNicoló Fusi, Oliver Stegle, Neil D Lawrence
Pageof 19

Showing results (1-10 of 181) with videos related to

Sort By:
Pageof 19
Nature Methods|September 14, 2023
Principles and challenges of modeling temporal and spatial omics dataBritta Velten, Oliver Stegle
Genome Biology|February 26, 2016
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expressionBarbara Rakitsch, Oliver Stegle
Genome Biology|May 13, 2020
Effects of the COVID-19 pandemic on life scientistsJan O Korbel, Oliver Stegle
Genome Biology|February 2, 2022
MUON: multimodal omics analysis frameworkDanila Bredikhin, Ilia Kats, Oliver Stegle
Nature Communications|June 26, 2015
A random forest approach to capture genetic effects in the presence of population structureJohannes Stephan, Oliver Stegle, Andreas Beyer
Science (New York, N.Y.)|October 7, 2017
Single-cell epigenomics: Recording the past and predicting the futureGavin Kelsey, Oliver Stegle, Wolf Reik
Nature Methods|March 20, 2018
SpatialDE: identification of spatially variable genesValentine Svensson, Sarah A Teichmann, Oliver Stegle
Genome Biology|December 15, 2019
Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype referenceYuanhua Huang, Davis J McCarthy, Oliver Stegle
Bioinformatics (Oxford, England)|June 30, 2016
GeneCodeq: quality score compression and improved genotyping using a Bayesian frameworkDaniel L Greenfield, Oliver Stegle, Alban Rrustemi
Plos Computational Biology|January 14, 2012
Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studiesNicoló Fusi, Oliver Stegle, Neil D Lawrence
Pageof 19