Britta Velten

4.3k total citations · 2 hit papers
13 papers, 1.4k citations indexed

About

Britta Velten is a scholar working on Molecular Biology, Genetics and Pathology and Forensic Medicine. According to data from OpenAlex, Britta Velten has authored 13 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 1 paper in Genetics and 1 paper in Pathology and Forensic Medicine. Recurrent topics in Britta Velten's work include Single-cell and spatial transcriptomics (4 papers), Bioinformatics and Genomic Networks (3 papers) and Gene expression and cancer classification (3 papers). Britta Velten is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), Bioinformatics and Genomic Networks (3 papers) and Gene expression and cancer classification (3 papers). Britta Velten collaborates with scholars based in Germany, United Kingdom and Switzerland. Britta Velten's co-authors include Oliver Stegle, Ricard Argelaguet, Damien Arnol, John C. Marioni, Wolfgang Huber, Sascha Dietrich, Thorsten Zenz, Florian Buettner, Danila Bredikhin and Jakob Wirbel and has published in prestigious journals such as Nature Communications, Bioinformatics and Nature Methods.

In The Last Decade

Britta Velten

13 papers receiving 1.4k citations

Hit Papers

Multi‐Omics Factor Analysis—a framework for unsupervised ... 2018 2026 2020 2023 2018 2020 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
    2018 664 citations Ricard Argelaguet, Britta Velten et al. Molecular Systems Biology profile →
  2. MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
    2020 432 citations Ricard Argelaguet, Damien Arnol et al. Genome biology profile →

Peers

Britta Velten
Damien Arnol United Kingdom
Vincent Gardeux Switzerland
Nikola S. Mueller Germany
Mahyar Sabripour United States
Rhonda Bacher United States
Luz García‐Alonso United Kingdom
Ricard Argelaguet United Kingdom
Monika Ray United States
Lei Xiong China
Damien Arnol United Kingdom
Britta Velten
Citations per year, relative to Britta Velten Britta Velten (= 1×) peers Damien Arnol

Countries citing papers authored by Britta Velten

Since Specialization
Citations

This map shows the geographic impact of Britta Velten's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Britta Velten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Britta Velten more than expected).

Fields of papers citing papers by Britta Velten

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Britta Velten. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Britta Velten. The network helps show where Britta Velten may publish in the future.

Co-authorship network of co-authors of Britta Velten

This figure shows the co-authorship network connecting the top 25 collaborators of Britta Velten. A scholar is included among the top collaborators of Britta Velten based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Britta Velten. Britta Velten is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Pepelnjak, Monika, Britta Velten, Umberto Capasso Palmiero, et al.. (2024). In situ analysis of osmolyte mechanisms of proteome thermal stabilization. Nature Chemical Biology. 20(8). 1053–1065. 16 indexed citations
2.
Braunger, Jana M. & Britta Velten. (2024). Guide assignment in single-cell CRISPR screens using crispat. Bioinformatics. 40(9). 1 indexed citations
3.
Flores, Ricardo O. Ramirez, Jan D. Lanzer, Daniel Dimitrov, Britta Velten, & Julio Sáez-Rodríguez. (2023). Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease. eLife. 12. 25 indexed citations
4.
Stegle, Oliver, et al.. (2023). FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution. Bioinformatics. 39(5). 12 indexed citations
5.
Lu, Junyan, et al.. (2023). The changing career paths of PhDs and postdocs trained at EMBL. eLife. 12. 1 indexed citations
6.
Velten, Britta & Oliver Stegle. (2023). Principles and challenges of modeling temporal and spatial omics data. Nature Methods. 20(10). 1462–1474. 38 indexed citations
7.
Velten, Britta, Jana M. Braunger, Ricard Argelaguet, et al.. (2022). Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO. Nature Methods. 19(2). 179–186. 78 indexed citations
8.
Lukas, Marina, Britta Velten, Leopold Sellner, et al.. (2020). Survey of ex vivo drug combination effects in chronic lymphocytic leukemia reveals synergistic drug effects and genetic dependencies. Leukemia. 34(11). 2934–2950. 17 indexed citations
9.
Cardoso-Moreira, Margarida, Ioannis Sarropoulos, Britta Velten, et al.. (2020). Developmental Gene Expression Differences between Humans and Mammalian Models. Cell Reports. 33(4). 108308–108308. 41 indexed citations
10.
Ibarra, Ignacio L., et al.. (2020). Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions. Nature Communications. 11(1). 124–124. 59 indexed citations
11.
Argelaguet, Ricard, Damien Arnol, Danila Bredikhin, et al.. (2020). MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data. Genome biology. 21(1). 111–111. 432 indexed citations breakdown →
12.
Argelaguet, Ricard, et al.. (2020). bioFAM/MOFA2: MOFA+ Release. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
13.
Argelaguet, Ricard, Britta Velten, Damien Arnol, et al.. (2018). Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets. Molecular Systems Biology. 14(6). e8124–e8124. 664 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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