Wouter J. Veneman

838 total citations
16 papers, 650 citations indexed

About

Wouter J. Veneman is a scholar working on Cell Biology, Molecular Biology and Immunology. According to data from OpenAlex, Wouter J. Veneman has authored 16 papers receiving a total of 650 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cell Biology, 5 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Wouter J. Veneman's work include Zebrafish Biomedical Research Applications (6 papers), Aquaculture disease management and microbiota (5 papers) and Immune Response and Inflammation (4 papers). Wouter J. Veneman is often cited by papers focused on Zebrafish Biomedical Research Applications (6 papers), Aquaculture disease management and microbiota (5 papers) and Immune Response and Inflammation (4 papers). Wouter J. Veneman collaborates with scholars based in Netherlands, Germany and France. Wouter J. Veneman's co-authors include Herman P. Spaink, Annemarie H. Meijer, Martina G. Vijver, Nadja R. Brun, Thijs Bosker, Jan de Sonneville, Oliver W. Stockhammer, Ron P. Dirks, Geert F. Wiegertjes and Zakia Kanwal and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Wouter J. Veneman

15 papers receiving 642 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Wouter J. Veneman Netherlands	11	198	180	162	159	72	16	650
Mónica Varela Netherlands	16	431 2.2×	190 1.1×	206 1.3×	77 0.5×	64 0.9×	21	799
Chi‐Yong Eom South Korea	14	73 0.4×	66 0.4×	237 1.5×	29 0.2×	29 0.4×	25	593
Zhijie Lu China	14	280 1.4×	51 0.3×	226 1.4×	61 0.4×	12 0.2×	46	633
Chengyu Hu China	18	471 2.4×	163 0.9×	375 2.3×	68 0.4×	21 0.3×	84	989
Paulo R. Dores-Silva Brazil	13	25 0.1×	42 0.2×	210 1.3×	26 0.2×	29 0.4×	32	386
Jun‐Yu Ma China	20	53 0.3×	70 0.4×	566 3.5×	32 0.2×	29 0.4×	59	1.1k
Katsuhide Miyake Japan	17	35 0.2×	27 0.1×	620 3.8×	65 0.4×	20 0.3×	50	902
Xin Tao China	16	215 1.1×	24 0.1×	483 3.0×	18 0.1×	15 0.2×	33	868
Jyoti Mishra India	11	32 0.2×	27 0.1×	217 1.3×	40 0.3×	109 1.5×	26	596
Jean‐Paul Lasserre France	13	55 0.3×	28 0.2×	401 2.5×	44 0.3×	32 0.4×	23	588

Countries citing papers authored by Wouter J. Veneman

Since Specialization

Citations

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

Fields of papers citing papers by Wouter J. Veneman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wouter J. Veneman. 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 Wouter J. Veneman. The network helps show where Wouter J. Veneman may publish in the future.

Co-authorship network of co-authors of Wouter J. Veneman

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

All Works

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16 of 16 papers shown

Rago, Daniela, Beata Joanna Lehka, Lea G. Hansen, et al.. (2024). Metabolic engineering of yeast for de novo production of kratom monoterpene indole alkaloids. Metabolic Engineering. 86. 135–146. 4 indexed citations

Jansen, Hans J., Mourad Ben Saïd, Wouter J. Veneman, et al.. (2024). Similarities between Ixodes ricinus and Ixodes inopinatus genomes and horizontal gene transfer from their endosymbionts. SHILAP Revista de lepidopterología. 6. 100229–100229.

Ding, Yi, Rubén Marín‐Juez, Wouter J. Veneman, et al.. (2020). Tuberculosis causes highly conserved metabolic changes in human patients, mycobacteria-infected mice and zebrafish larvae. Scientific Reports. 10(1). 11635–11635. 19 indexed citations

Jarque, Sergio, Éva Fetter, Wouter J. Veneman, et al.. (2018). An automated screening method for detecting compounds with goitrogenic activity using transgenic zebrafish embryos. PLoS ONE. 13(8). e0203087–e0203087. 23 indexed citations

Veneman, Wouter J., Herman P. Spaink, Nadja R. Brun, Thijs Bosker, & Martina G. Vijver. (2017). Pathway analysis of systemic transcriptome responses to injected polystyrene particles in zebrafish larvae. Aquatic Toxicology. 190. 112–120. 159 indexed citations

Guo, Yuanhao, Wouter J. Veneman, Herman P. Spaink, & Fons J. Verbeek. (2017). Three-dimensional reconstruction and measurements of zebrafish larvae from high-throughput axial-view in vivo imaging. Biomedical Optics Express. 8(5). 2611–2611. 25 indexed citations

Ent, Wietske van der, Wouter J. Veneman, Arwin Groenewoud, et al.. (2016). Automation of Technology for Cancer Research. Advances in experimental medicine and biology. 916. 315–332. 6 indexed citations

Mal, Joyabrata, Wouter J. Veneman, Y.V. Nancharaiah, et al.. (2016). A comparison of fate and toxicity of selenite, biogenically, and chemically synthesized selenium nanoparticles to zebrafish (Danio rerio) embryogenesis. Nanotoxicology. 11(1). 87–97. 68 indexed citations

Spaink, Herman P., Péter Rácz, Anita Ordas, et al.. (2015). Automated zebrafish toxicology screening: Effect assessment and uptake studies. Toxicology Letters. 238(2). S54–S54. 1 indexed citations

10.

Guo, Yuanhao, Wouter J. Veneman, Herman P. Spaink, & Fons J. Verbeek. (2015). Silhouette-based 3D model for zebrafish high-throughput imaging. Leiden Repository (Leiden University). 403–408. 2 indexed citations

11.

Veneman, Wouter J., Rubén Marín‐Juez, Jan de Sonneville, et al.. (2014). Establishment and Optimization of a High Throughput Setup to Study <em>Staphylococcus epidermidis</em> and <em>Mycobacterium marinum</em> Infection as a Model for Drug Discovery. Journal of Visualized Experiments. e51649–e51649. 22 indexed citations

12.

Kanwal, Zakia, Geert F. Wiegertjes, Wouter J. Veneman, Annemarie H. Meijer, & Herman P. Spaink. (2014). Comparative studies of Toll-like receptor signalling using zebrafish. Developmental & Comparative Immunology. 46(1). 35–52. 75 indexed citations

13.

Veneman, Wouter J., Jan de Sonneville, Anita Ordas, et al.. (2014). Analysis of RNAseq datasets from a comparative infectious disease zebrafish model using GeneTiles bioinformatics. Immunogenetics. 67(3). 135–147. 14 indexed citations

14.

Spaink, Herman P., Chao Cui, Małgorzata Wiweger, et al.. (2013). Robotic injection of zebrafish embryos for high-throughput screening in disease models. Methods. 62(3). 246–254. 81 indexed citations

15.

Veneman, Wouter J., Oliver W. Stockhammer, Leonie de Boer, et al.. (2013). A zebrafish high throughput screening system used for Staphylococcus epidermidis infection marker discovery. BMC Genomics. 14(1). 255–255. 57 indexed citations

16.

Carvalho, Ralph, Jan de Sonneville, Oliver W. Stockhammer, et al.. (2011). A High-Throughput Screen for Tuberculosis Progression. PLoS ONE. 6(2). e16779–e16779. 94 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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