Marella de Bruijn

12.4k total citations · 2 hit papers
67 papers, 7.2k citations indexed

About

Marella de Bruijn is a scholar working on Cell Biology, Molecular Biology and Immunology. According to data from OpenAlex, Marella de Bruijn has authored 67 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Cell Biology, 35 papers in Molecular Biology and 30 papers in Immunology. Recurrent topics in Marella de Bruijn's work include Zebrafish Biomedical Research Applications (43 papers), Immune cells in cancer (15 papers) and Epigenetics and DNA Methylation (14 papers). Marella de Bruijn is often cited by papers focused on Zebrafish Biomedical Research Applications (43 papers), Immune cells in cancer (15 papers) and Epigenetics and DNA Methylation (14 papers). Marella de Bruijn collaborates with scholars based in United Kingdom, United States and Netherlands. Marella de Bruijn's co-authors include Elaine Dzierzak, Nancy A. Speck, Emanuele Azzoni, Frédéric Geissmann, Hannah Garner, Christian Schulz, Céline Trouillet, Lucile Crozet, Kay Klapproth and Elisa Gomez Perdiguero and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Marella de Bruijn

67 papers receiving 7.1k citations

Hit Papers

Tissue-resident macrophages originate from yolk-sac-deriv... 2010 2026 2015 2020 2014 2010 500 1000 1.5k

Peers

Marella de Bruijn
E. Camilla Forsberg United States
Kathleen E. McGrath United States
Claus Nerlov United Kingdom
Nancy A. Speck United States
Karen Carver-Moore United States
H. Leighton Grimes United States
E. Camilla Forsberg United States
Marella de Bruijn
Citations per year, relative to Marella de Bruijn Marella de Bruijn (= 1×) peers E. Camilla Forsberg

Countries citing papers authored by Marella de Bruijn

Since Specialization
Citations

This map shows the geographic impact of Marella de Bruijn'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 Marella de Bruijn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marella de Bruijn more than expected).

Fields of papers citing papers by Marella de Bruijn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marella de Bruijn. 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 Marella de Bruijn. The network helps show where Marella de Bruijn may publish in the future.

Co-authorship network of co-authors of Marella de Bruijn

This figure shows the co-authorship network connecting the top 25 collaborators of Marella de Bruijn. A scholar is included among the top collaborators of Marella de Bruijn 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 Marella de Bruijn. Marella de Bruijn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mailhé, Marie-Pierre, João P. Pereira, Emanuele Azzoni, et al.. (2025). Spatiotemporal dynamics of fetal liver hematopoietic niches. The Journal of Experimental Medicine. 222(2). 4 indexed citations
2.
Kurochkin, Ilia, Anna Rydström, Christina Rode, et al.. (2023). GATA2 mitotic bookmarking is required for definitive haematopoiesis. Nature Communications. 14(1). 4645–4645. 12 indexed citations
3.
Imaz-Rosshandler, Iván, Christina Rode, Carolina Guibentif, et al.. (2023). Tracking early mammalian organogenesis – prediction and validation of differentiation trajectories at whole organism scale. Development. 151(3). 10 indexed citations
4.
Owens, Dominic D. G., Giorgio Anselmi, A. Marieke Oudelaar, et al.. (2022). Dynamic Runx1 chromatin boundaries affect gene expression in hematopoietic development. Nature Communications. 13(1). 773–773. 18 indexed citations
5.
Harland, Luke, Claire Simon, Anna D. Senft, et al.. (2021). The T-box transcription factor Eomesodermin governs haemogenic competence of yolk sac mesodermal progenitors. Nature Cell Biology. 23(1). 61–74. 21 indexed citations
6.
Harman, Joe, Ross Thorne, Marta Tapia, et al.. (2021). A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes. Genome Research. 31(7). 1159–1173. 17 indexed citations
7.
Azzoni, Emanuele, Vincent Frontera, Giorgio Anselmi, et al.. (2021). The onset of circulation triggers a metabolic switch required for endothelial to hematopoietic transition. Cell Reports. 37(11). 110103–110103. 19 indexed citations
8.
Neo, Wen Hao, Christopher A.G. Booth, Emanuele Azzoni, et al.. (2018). Cell-extrinsic hematopoietic impact of Ezh2 inactivation in fetal liver endothelial cells. Blood. 131(20). 2223–2234. 22 indexed citations
9.
Bruijn, Marella de, et al.. (2017). Disruption of the aortic wall by coelomic lining-derived mesenchymal cells accompanies the onset of aortic hematopoiesis. The International Journal of Developmental Biology. 61(3-4-5). 329–335. 4 indexed citations
10.
Migueles, Rosa Portero, Louise Shaw, Neil P. Rodrigues, et al.. (2017). Transcriptional regulation of Hhex in hematopoiesis and hematopoietic stem cell ontogeny. Developmental Biology. 424(2). 236–245. 11 indexed citations
11.
Pereira, Carlos‐Filipe, Betty Chang, Jeffrey M. Bernitz, et al.. (2016). Hematopoietic Reprogramming In Vitro Informs In Vivo Identification of Hemogenic Precursors to Definitive Hematopoietic Stem Cells. Developmental Cell. 36(5). 525–539. 29 indexed citations
12.
Perdiguero, Elisa Gomez, Kay Klapproth, Christian Schulz, et al.. (2015). Tissue-resident macrophages originate from yolk sac-derived erythro-myeloid progenitors. Experimental Hematology. 43(9). S64–S64. 39 indexed citations
13.
Mirshekar-Syahkal, Bahar, Esther Haak, Kevin Harvey, et al.. (2012). Dlk1 is a negative regulator of emerging hematopoietic stem and progenitor cells. Haematologica. 98(2). 163–171. 41 indexed citations
14.
Bruijn, Marella de, et al.. (2010). Hematopoietic stem cell emergence in the conceptus and the role of Runx1. The International Journal of Developmental Biology. 54(6-7). 1151–1163. 65 indexed citations
15.
Bruijn, Marella de, Hanna Mikkola, Hans‐Willem Snoeck, & Gordon Keller. (2008). Highlights from Philadelphia: ISSCR 2008. Cell stem cell. 3(3). 259–264. 1 indexed citations
16.
Jaffredo, Thierry, Wade Nottingham, Kate Liddiard, et al.. (2005). From hemangioblast to hematopoietic stem cell: An endothelial connection?. Experimental Hematology. 33(9). 1029–1040. 94 indexed citations
17.
North, Trista E., Marella de Bruijn, Terryl Stacy, et al.. (2002). Runx1 Expression Marks Long-Term Repopulating Hematopoietic Stem Cells in the Midgestation Mouse Embryo. Immunity. 16(5). 661–672. 452 indexed citations
18.
Ma, Xiaoqian, Marella de Bruijn, Catherine Robin, et al.. (2002). Expression of the Ly‐6A (Sca‐1) lacZ transgene in mouse haematopoietic stem cells and embryos. British Journal of Haematology. 116(2). 401–408. 22 indexed citations
19.
Whyatt, David, Alar Karis, Rita Ferreira, et al.. (2000). An intrinsic but cell-nonautonomous defect in GATA-1-overexpressing mouse erythroid cells. Nature. 406(6795). 519–524. 91 indexed citations
20.
Bruijn, Marella de, Walentina A. T. Slieker, Johannes C.M. van der Loo, et al.. (1994). Distinct mouse bone marrow macrophage precursors identified by differential expression of ER‐MP12 and ER‐MP20 antigens. European Journal of Immunology. 24(10). 2279–2284. 122 indexed citations

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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