Velten Group Multi-factorial data analysis & machine learning for the life sciences

Publications

Here you can find our recent publications.

Selected

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber, Oliver Stegle
Molecular Systems Biology   ·   18 Jun 2018   ·   doi:10.15252/msb.20178124
MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in an unsupervised fashion
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO
Britta Velten, Jana M. Braunger, Ricard Argelaguet, Damien Arnol, Jakob Wirbel, Danila Bredikhin, Georg Zeller, Oliver Stegle
Nature Methods   ·   13 Jan 2022   ·   doi:10.1038/s41592-021-01343-9
MEFISTO is a unsupervised method to integrate multi-modal data with continuous structures among the samples, e.g. in spatial or temporal data.
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution
Florin C Walter, Oliver Stegle, Britta Velten
Bioinformatics   ·   11 Apr 2023   ·   doi:10.1093/bioinformatics/btad183
FISHFactor identifies spatial gene expression patterns at subcellular resolution

All

2024

Guide assignment in single-cell CRISPR screens using crispat
Guide assignment in single-cell CRISPR screens using crispat
Jana M. Braunger, Britta Velten
Cold Spring Harbor Laboratory   ·   10 May 2024   ·   doi:10.1101/2024.05.06.592692
In situ analysis of osmolyte mechanisms of proteome thermal stabilization
In situ analysis of osmolyte mechanisms of proteome thermal stabilization
Monika Pepelnjak, Britta Velten, Nicolas Näpflin, Tatjana von Rosen, Umberto Capasso Palmiero, ..., Paolo Arosio, Eilika Weber-Ban, Natalie de Souza, Wolfgang Huber, Paola Picotti
Nature Chemical Biology   ·   29 Feb 2024   ·   doi:10.1038/s41589-024-01568-7

2023

The changing career paths of PhDs and postdocs trained at EMBL
The changing career paths of PhDs and postdocs trained at EMBL
Junyan Lu, Britta Velten, Bernd Klaus, Mauricio Ramm, Wolfgang Huber, Rachel Coulthard-Graf
eLife   ·   23 Nov 2023   ·   doi:10.7554/elife.78706
Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease
Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease
Ricardo Omar Ramirez Flores, Jan David Lanzer, Daniel Dimitrov, Britta Velten, Julio Saez-Rodriguez
eLife   ·   22 Nov 2023   ·   doi:10.7554/elife.93161
Principles and challenges of modeling temporal and spatial omics data
Principles and challenges of modeling temporal and spatial omics data
Britta Velten, Oliver Stegle
Nature Methods   ·   14 Sep 2023   ·   doi:10.1038/s41592-023-01992-y
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution
FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution
Florin C Walter, Oliver Stegle, Britta Velten
Bioinformatics   ·   11 Apr 2023   ·   doi:10.1093/bioinformatics/btad183
FISHFactor identifies spatial gene expression patterns at subcellular resolution
Spatial multiomics map of trophoblast development in early pregnancy
Spatial multiomics map of trophoblast development in early pregnancy
Anna Arutyunyan, Kenny Roberts, Kevin Troulé, Frederick C. K. Wong, Megan A. Sheridan, ..., Omer Ali Bayraktar, Ashley Moffett, Oliver Stegle, Margherita Y. Turco, Roser Vento-Tormo
Nature   ·   29 Mar 2023   ·   doi:10.1038/s41586-023-05869-0

2022

Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO
Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO
Britta Velten, Jana M. Braunger, Ricard Argelaguet, Damien Arnol, Jakob Wirbel, Danila Bredikhin, Georg Zeller, Oliver Stegle
Nature Methods   ·   13 Jan 2022   ·   doi:10.1038/s41592-021-01343-9
MEFISTO is a unsupervised method to integrate multi-modal data with continuous structures among the samples, e.g. in spatial or temporal data.

2020

Developmental Gene Expression Differences between Humans and Mammalian Models
Developmental Gene Expression Differences between Humans and Mammalian Models
Margarida Cardoso-Moreira, Ioannis Sarropoulos, Britta Velten, Matthew Mort, David N. Cooper, Wolfgang Huber, Henrik Kaessmann
Cell Reports   ·   01 Oct 2020   ·   doi:10.1016/j.celrep.2020.108308
Survey of ex vivo drug combination effects in chronic lymphocytic leukemia reveals synergistic drug effects and genetic dependencies
Survey of ex vivo drug combination effects in chronic lymphocytic leukemia reveals synergistic drug effects and genetic dependencies
Marina Lukas, Britta Velten, Leopold Sellner, Katarzyna Tomska, Jennifer Hüellein, ..., Alexander Jethwa, Hanibal Bohnenberger, Junyan Lu, Wolfgang Huber, Thorsten Zenz
Leukemia   ·   13 May 2020   ·   doi:10.1038/s41375-020-0846-5
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
Ricard Argelaguet, Damien Arnol, Danila Bredikhin, Yonatan Deloro, Britta Velten, John C. Marioni, Oliver Stegle
Genome Biology   ·   11 May 2020   ·   doi:10.1186/s13059-020-02015-1
Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions
Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions
Ignacio L. Ibarra, Nele M. Hollmann, Bernd Klaus, Sandra Augsten, Britta Velten, Janosch Hennig, Judith B. Zaugg
Nature Communications   ·   08 Jan 2020   ·   doi:10.1038/s41467-019-13888-7

2019

Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes
Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes
Britta Velten, Wolfgang Huber
Biostatistics   ·   09 Oct 2019   ·   doi:10.1093/biostatistics/kxz034
Gene expression across mammalian organ development
Gene expression across mammalian organ development
Margarida Cardoso-Moreira, Jean Halbert, Delphine Valloton, Britta Velten, Chunyan Chen, ..., Wolfgang Huber, Julie Baker, Simon Anders, Yong E. Zhang, Henrik Kaessmann
Nature   ·   26 Jun 2019   ·   doi:10.1038/s41586-019-1338-5

2018

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber, Oliver Stegle
Molecular Systems Biology   ·   18 Jun 2018   ·   doi:10.15252/msb.20178124
MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in an unsupervised fashion

2017

Drug-perturbation-based stratification of blood cancer
Drug-perturbation-based stratification of blood cancer
Sascha Dietrich, Małgorzata Oleś, Junyan Lu, Leopold Sellner, Simon Anders, ..., Jan Dürig, Ingo Ringshausen, Marc Zapatka, Wolfgang Huber, Thorsten Zenz
Journal of Clinical Investigation   ·   11 Dec 2017   ·   doi:10.1172/jci93801