Bram Piersma

1.4k total citations · 2 hit papers
9 papers, 1.0k citations indexed

About

Bram Piersma is a scholar working on Cell Biology, Surgery and Molecular Biology. According to data from OpenAlex, Bram Piersma has authored 9 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cell Biology, 4 papers in Surgery and 3 papers in Molecular Biology. Recurrent topics in Bram Piersma's work include Hippo pathway signaling and YAP/TAZ (4 papers), Genital Health and Disease (4 papers) and Connective tissue disorders research (2 papers). Bram Piersma is often cited by papers focused on Hippo pathway signaling and YAP/TAZ (4 papers), Genital Health and Disease (4 papers) and Connective tissue disorders research (2 papers). Bram Piersma collaborates with scholars based in Netherlands, Germany and Denmark. Bram Piersma's co-authors include Ruud A. Bank, Mary-Kate Hayward, Valerie M. Weaver, Miriam Boersema, Paul M. N. Werker, Boris Hinz, Marike Marjolijn van Beuge, Stellar Boo, Rutger A. F. Gjaltema and Anna M. Leliveld and has published in prestigious journals such as Nature Communications, Scientific Reports and American Journal Of Pathology.

In The Last Decade

Bram Piersma

9 papers receiving 1.0k citations

Hit Papers

Fibrosis and cancer: A strained relationship 2015 2026 2018 2022 2020 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bram Piersma Netherlands 7 399 292 264 145 144 9 1.0k
Franco Klingberg Canada 5 373 0.9× 254 0.9× 128 0.5× 219 1.5× 220 1.5× 6 1.1k
Yoshiya Shimao Japan 15 508 1.3× 255 0.9× 350 1.3× 168 1.2× 96 0.7× 43 1.2k
Michael Ginsberg United States 16 912 2.3× 287 1.0× 156 0.6× 211 1.5× 225 1.6× 24 1.5k
Xiangwei Huang China 10 414 1.0× 279 1.0× 147 0.6× 405 2.8× 139 1.0× 16 1.2k
Salman Rahman United States 17 792 2.0× 216 0.7× 162 0.6× 137 0.9× 215 1.5× 41 1.5k
Seiji Mori Japan 20 490 1.2× 104 0.4× 289 1.1× 103 0.7× 179 1.2× 45 1000
Guangpei Hou Canada 18 415 1.0× 307 1.1× 180 0.7× 110 0.8× 113 0.8× 25 1.2k
Monika Hermansson United Kingdom 15 437 1.1× 150 0.5× 206 0.8× 152 1.0× 135 0.9× 19 1.6k
Melanie Mumau United States 8 638 1.6× 131 0.4× 228 0.9× 378 2.6× 306 2.1× 19 1.2k
Dongmiao Wang China 23 976 2.4× 242 0.8× 420 1.6× 127 0.9× 96 0.7× 63 1.7k

Countries citing papers authored by Bram Piersma

Since Specialization
Citations

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

Fields of papers citing papers by Bram Piersma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bram Piersma

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

All Works

9 of 9 papers shown
1.
Kamali, Zoha, Michael Ng, Dmitriy Drichel, et al.. (2024). A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren’s disease. Nature Communications. 15(1). 199–199. 6 indexed citations
2.
Werker, Paul M. N., et al.. (2022). Verteporfin ameliorates fibrotic aspects of Dupuytren’s disease nodular fibroblasts irrespective the activation state of the cells. Scientific Reports. 12(1). 13940–13940. 3 indexed citations
3.
Piersma, Bram, Mary-Kate Hayward, & Valerie M. Weaver. (2020). Fibrosis and cancer: A strained relationship. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1873(2). 188356–188356. 440 indexed citations breakdown →
4.
Bigaeva, Emilia, Henricus A. M. Mutsaers, Bram Piersma, et al.. (2019). Inhibition of tyrosine kinase receptor signaling attenuates fibrogenesis in an ex vivo model of human renal fibrosis. American Journal of Physiology-Renal Physiology. 318(1). F117–F134. 12 indexed citations
5.
Piersma, Bram & Ruud A. Bank. (2019). Collagen cross-linking mediated by lysyl hydroxylase 2: an enzymatic battlefield to combat fibrosis. Essays in Biochemistry. 63(3). 377–387. 64 indexed citations
6.
Piersma, Bram, et al.. (2018). αII-spectrin and βII-spectrin do not affect TGFβ1-induced myofibroblast differentiation. Cell and Tissue Research. 374(1). 165–175. 4 indexed citations
7.
Piersma, Bram, et al.. (2017). Ascorbic acid promotes a TGFβ1-induced myofibroblast phenotype switch. Physiological Reports. 5(17). e13324–e13324. 35 indexed citations
8.
Piersma, Bram, Paul M. N. Werker, Stellar Boo, et al.. (2015). YAP1 Is a Driver of Myofibroblast Differentiation in Normal and Diseased Fibroblasts. American Journal Of Pathology. 185(12). 3326–3337. 107 indexed citations
9.
Piersma, Bram, Ruud A. Bank, & Miriam Boersema. (2015). Signaling in Fibrosis: TGF-β, WNT, and YAP/TAZ Converge. Frontiers in Medicine. 2. 59–59. 351 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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