Eva Schut

2.0k total citations · 1 hit paper
15 papers, 1.3k citations indexed

About

Eva Schut is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Eva Schut has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 9 papers in Oncology and 8 papers in Genetics. Recurrent topics in Eva Schut's work include BRCA gene mutations in cancer (5 papers), CRISPR and Genetic Engineering (4 papers) and DNA Repair Mechanisms (3 papers). Eva Schut is often cited by papers focused on BRCA gene mutations in cancer (5 papers), CRISPR and Genetic Engineering (4 papers) and DNA Repair Mechanisms (3 papers). Eva Schut collaborates with scholars based in Netherlands, United Kingdom and Germany. Eva Schut's co-authors include Jos Jonkers, Eline van der Burg, Lodewyk F.A. Wessels, Sjors M. Kas, Sjoerd Klarenbeek, Anne Paulien Drenth, Rinske Drost, Ingrid van der Heijden, Henne Holstege and Bastiaan Evers and has published in prestigious journals such as Nature, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Eva Schut

15 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasis

2019 361 citations Max D. Wellenstein, Seth B. Coffelt et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eva Schut Netherlands	13	879	707	269	228	201	15	1.3k
Elizabeth Ruth Plummer United Kingdom	19	836 1.0×	961 1.4×	152 0.6×	181 0.8×	137 0.7×	69	1.3k
Jessica Frankum United Kingdom	14	843 1.0×	697 1.0×	146 0.5×	184 0.8×	80 0.4×	21	1.1k
Sabrina Giavara Italy	4	1.1k 1.2×	826 1.2×	237 0.9×	168 0.7×	92 0.5×	5	1.4k
Eline van der Burg Netherlands	13	1.2k 1.3×	1.3k 1.8×	342 1.3×	262 1.1×	134 0.7×	19	1.7k
Rinske Drost Netherlands	12	1.0k 1.2×	794 1.1×	394 1.5×	170 0.7×	64 0.3×	14	1.2k
Simona Blotta United States	12	663 0.8×	452 0.6×	143 0.5×	141 0.6×	189 0.9×	22	1.0k
Paul M. Moseley United Kingdom	22	796 0.9×	616 0.9×	111 0.4×	314 1.4×	88 0.4×	45	1.1k
Shaveta Vinayak United States	15	429 0.5×	790 1.1×	160 0.6×	351 1.5×	193 1.0×	45	1.2k
Bose Kochupurakkal United States	16	1.0k 1.2×	810 1.1×	97 0.4×	183 0.8×	117 0.6×	44	1.4k
Anna L Olsen United Kingdom	7	727 0.8×	535 0.8×	95 0.4×	124 0.5×	213 1.1×	9	964

Countries citing papers authored by Eva Schut

Since Specialization

Citations

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

Fields of papers citing papers by Eva Schut

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eva Schut. 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 Eva Schut. The network helps show where Eva Schut may publish in the future.

Co-authorship network of co-authors of Eva Schut

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

All Works

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15 of 15 papers shown

Henneman, Linda, Anne Paulien Drenth, Eva Schut, et al.. (2019). Exogenous ERα Expression in the Mammary Epithelium Decreases Over Time and Does Not Contribute to p53-Deficient Mammary Tumor Formation in Mice. Journal of Mammary Gland Biology and Neoplasia. 24(4). 305–321. 3 indexed citations

Wellenstein, Max D., Seth B. Coffelt, Danique E. M. Duits, et al.. (2019). Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasis. Nature. 572(7770). 538–542. 361 indexed citations breakdown →

Kas, Sjors M., Julian R. de Ruiter, Koen Schipper, et al.. (2018). Transcriptomics and Transposon Mutagenesis Identify Multiple Mechanisms of Resistance to the FGFR Inhibitor AZD4547. Cancer Research. 78(19). 5668–5679. 30 indexed citations

Kas, Sjors M., Julian R. de Ruiter, Koen Schipper, et al.. (2017). Insertional mutagenesis identifies drivers of a novel oncogenic pathway in invasive lobular breast carcinoma. Nature Genetics. 49(8). 1219–1230. 55 indexed citations

Ruiter, Julian R. de, Sjors M. Kas, Eva Schut, et al.. (2017). Identifying transposon insertions and their effects from RNA-sequencing data. Nucleic Acids Research. 45(12). 7064–7077. 6 indexed citations

Annunziato, Stefano, Sjors M. Kas, Micha Nethe, et al.. (2016). Modeling invasive lobular breast carcinoma by CRISPR/Cas9-mediated somatic genome editing of the mammary gland. Genes & Development. 30(12). 1470–1480. 100 indexed citations

Boelens, Mirjam C., Micha Nethe, Sjoerd Klarenbeek, et al.. (2016). PTEN Loss in E-Cadherin-Deficient Mouse Mammary Epithelial Cells Rescues Apoptosis and Results in Development of Classical Invasive Lobular Carcinoma. Cell Reports. 16(8). 2087–2101. 37 indexed citations

Groenendijk, Floris H., Wouter W. Mellema, Eline van der Burg, et al.. (2014). Sorafenib synergizes with metformin in NSCLC through AMPK pathway activation. International Journal of Cancer. 136(6). 1434–1444. 61 indexed citations

Drost, Rinske, Peter Bouwman, Sven Rottenberg, et al.. (2011). BRCA1 RING Function Is Essential for Tumor Suppression but Dispensable for Therapy Resistance. Cancer Cell. 20(6). 797–809. 197 indexed citations

10.

Koudijs, Marco J., Christiaan Klijn, Jaap Kool, et al.. (2011). High-throughput semiquantitative analysis of insertional mutations in heterogeneous tumors. Genome Research. 21(12). 2181–2189. 32 indexed citations

11.

Varela, Ignacio, Christiaan Klijn, P. J. Stephens, et al.. (2010). Somatic structural rearrangements in genetically engineered mouse mammary tumors. Genome biology. 11(10). R100–R100. 19 indexed citations

12.

Holstege, Henne, Arno Velds, Xiaoling Liu, et al.. (2010). Cross-species comparison of aCGH data from mouse and human BRCA1- and BRCA2-mutated breast cancers. BMC Cancer. 10(1). 455–455. 32 indexed citations

13.

Evers, Bastiaan, Eva Schut, Eline van der Burg, et al.. (2009). A High-Throughput Pharmaceutical Screen Identifies Compounds with Specific Toxicity against BRCA2-Deficient Tumors. Clinical Cancer Research. 16(1). 99–108. 66 indexed citations

14.

Evers, Bastiaan, Ewoud N. Speksnijder, Eva Schut, et al.. (2009). A tissue reconstitution model to study cancer cell‐intrinsic and ‐extrinsic factors in mammary tumourigenesis. The Journal of Pathology. 220(1). 34–44. 12 indexed citations

15.

Evers, Bastiaan, Rinske Drost, Eva Schut, et al.. (2008). Selective Inhibition of BRCA2-Deficient Mammary Tumor Cell Growth by AZD2281 and Cisplatin. Clinical Cancer Research. 14(12). 3916–3925. 259 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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