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Britta Velten

Showing results (1-10 of 18) 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
Biostatistics (Oxford, England)|October 10, 2019
Adaptive penalization in high-dimensional regression and classification with external covariates using variational BayesBritta Velten, Wolfgang Huber
Bioinformatics (Oxford, England)|September 6, 2024
Guide assignment in single-cell CRISPR screens using crispatJana M Braunger, Britta Velten
Bioinformatics (Oxford, England)|April 11, 2023
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolutionFlorin C Walter, Oliver Stegle, Britta Velten
Elife|November 23, 2023
The changing career paths of PhDs and postdocs trained at EMBLJunyan Lu, Britta Velten, Bernd Klaus, et al.
Elife|November 22, 2023
Multicellular factor analysis of single-cell data for a tissue-centric understanding of diseaseRicardo Omar Ramirez Flores, Jan David Lanzer, Daniel Dimitrov, et al.
Genome Biology|May 13, 2020
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell dataRicard Argelaguet, Damien Arnol, Danila Bredikhin, et al.
Cell Reports|October 28, 2020
Developmental Gene Expression Differences between Humans and Mammalian ModelsMargarida Cardoso-Moreira, Ioannis Sarropoulos, Britta Velten, et al.
Nature Methods|January 14, 2022
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTOBritta Velten, Jana M Braunger, Ricard Argelaguet, et al.
Nature Communications|January 9, 2020
Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactionsIgnacio L Ibarra, Nele M Hollmann, Bernd Klaus, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
Nature Methods|September 14, 2023
Principles and challenges of modeling temporal and spatial omics dataBritta Velten, Oliver Stegle
Biostatistics (Oxford, England)|October 10, 2019
Adaptive penalization in high-dimensional regression and classification with external covariates using variational BayesBritta Velten, Wolfgang Huber
Bioinformatics (Oxford, England)|September 6, 2024
Guide assignment in single-cell CRISPR screens using crispatJana M Braunger, Britta Velten
Bioinformatics (Oxford, England)|April 11, 2023
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolutionFlorin C Walter, Oliver Stegle, Britta Velten
Elife|November 23, 2023
The changing career paths of PhDs and postdocs trained at EMBLJunyan Lu, Britta Velten, Bernd Klaus, et al.
Elife|November 22, 2023
Multicellular factor analysis of single-cell data for a tissue-centric understanding of diseaseRicardo Omar Ramirez Flores, Jan David Lanzer, Daniel Dimitrov, et al.
Genome Biology|May 13, 2020
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell dataRicard Argelaguet, Damien Arnol, Danila Bredikhin, et al.
Cell Reports|October 28, 2020
Developmental Gene Expression Differences between Humans and Mammalian ModelsMargarida Cardoso-Moreira, Ioannis Sarropoulos, Britta Velten, et al.
Nature Methods|January 14, 2022
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTOBritta Velten, Jana M Braunger, Ricard Argelaguet, et al.
Nature Communications|January 9, 2020
Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactionsIgnacio L Ibarra, Nele M Hollmann, Bernd Klaus, et al.
Pageof 2