Jan Polman

3.3k total citations · 1 hit paper
17 papers, 2.7k citations indexed

About

Jan Polman is a scholar working on Molecular Biology, Computational Theory and Mathematics and Reproductive Medicine. According to data from OpenAlex, Jan Polman has authored 17 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 5 papers in Reproductive Medicine. Recurrent topics in Jan Polman's work include Computational Drug Discovery Methods (7 papers), Biomedical Text Mining and Ontologies (4 papers) and Ovarian function and disorders (3 papers). Jan Polman is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Biomedical Text Mining and Ontologies (4 papers) and Ovarian function and disorders (3 papers). Jan Polman collaborates with scholars based in Netherlands, United States and United Kingdom. Jan Polman's co-authors include Sietse Mosselman, R. Dijkema, Carlos Simón, J.A. Horcajadas, A. Riesewijk, António Pellicer, H. Bunschoten, Marcel van Duin, R. John Aitken and James Brindle and has published in prestigious journals such as Nucleic Acids Research, FEBS Letters and BMC Bioinformatics.

In The Last Decade

Jan Polman

16 papers receiving 2.6k citations

Hit Papers

ERβ: Identification and characterization of a novel human... 1996 2026 2006 2016 1996 500 1000 1.5k
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. ERβ: Identification and characterization of a novel human estrogen receptor
    1996 1.9k citations Sietse Mosselman, Jan Polman et al. FEBS Letters profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Polman Netherlands 13 1.7k 924 683 410 402 17 2.7k
Gary Means United States 18 1.4k 0.9× 877 0.9× 421 0.6× 242 0.6× 339 0.8× 32 2.6k
Guojun Cheng Sweden 15 1.9k 1.2× 1.1k 1.2× 352 0.5× 239 0.6× 760 1.9× 17 3.2k
D. P. McDonnell United States 9 1.4k 0.9× 608 0.7× 427 0.6× 143 0.3× 284 0.7× 13 1.9k
J. Dinny Graham Australia 30 1.9k 1.1× 1.1k 1.2× 494 0.7× 266 0.6× 886 2.2× 57 3.2k
Jay Wimalasena United States 30 1.0k 0.6× 1.7k 1.8× 475 0.7× 467 1.1× 942 2.3× 59 3.4k
Viroj Boonyaratanakornkit United States 20 1.4k 0.9× 1.0k 1.1× 373 0.5× 147 0.4× 545 1.4× 37 2.4k
B W O'Malley United States 14 1.5k 0.9× 900 1.0× 379 0.6× 98 0.2× 323 0.8× 14 2.1k
Glenn S. Takimoto United States 24 2.6k 1.5× 1.7k 1.8× 519 0.8× 131 0.3× 745 1.9× 42 3.6k
Bonnie J. Deroo United States 20 1.3k 0.8× 1.9k 2.0× 307 0.4× 346 0.8× 964 2.4× 29 3.9k
Deepak S. Lala United States 22 2.0k 1.2× 1.9k 2.1× 452 0.7× 298 0.7× 293 0.7× 41 3.3k

Countries citing papers authored by Jan Polman

Since Specialization
Citations

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

Fields of papers citing papers by Jan Polman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Polman

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

All Works

17 of 17 papers shown
1.
2.
Jennen, Danyel, Jan Polman, Joost van Delft, et al.. (2014). Data-integration of endpoints, cheminformatics and omics. Toxicology Letters. 229. S4–S5. 3 indexed citations
3.
Fleuren, Wilco, Stefan Verhoeven, Raoul Frijters, et al.. (2011). CoPub update: CoPub 5.0 a text mining system to answer biological questions. Nucleic Acids Research. 39(suppl). W450–W454. 32 indexed citations
4.
Elferink, Marieke G. L., Peter Olinga, Susanne Bauerschmidt, et al.. (2011). Gene expression analysis of precision-cut human liver slices indicates stable expression of ADME-Tox related genes. Toxicology and Applied Pharmacology. 253(1). 57–69. 49 indexed citations
5.
Elferink, Marieke G. L., Peter Olinga, Susanne Bauerschmidt, et al.. (2010). Gene expression analysis of precision cut human liver slices indicate stable expression of ADME-Tox related genes. Toxicology Letters. 196. S215–S215. 1 indexed citations
6.
Olinga, Peter, Annelies L. Draaisma, Marjolijn T. Merema, et al.. (2008). Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity. Toxicology and Applied Pharmacology. 229(3). 300–309. 70 indexed citations
7.
Frijters, Raoul, et al.. (2008). CoPub: a literature-based keyword enrichment tool for microarray data analysis. Nucleic Acids Research. 36(Web Server). W406–W410. 66 indexed citations
8.
Kruse, Jacqueline, J. Peter Svensson, Merei Huigsloot, et al.. (2007). A portrait of cisplatin-induced transcriptional changes in mouse embryonic stem cells reveals a dominant p53-like response. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 617(1-2). 58–70. 16 indexed citations
9.
Frijters, Raoul, Stefan Verhoeven, Wynand Alkema, René van Schaik, & Jan Polman. (2007). Literature-Based Compound Profiling: Application to Toxicogenomics. Pharmacogenomics. 8(11). 1521–1534. 17 indexed citations
10.
Alako, Blaise, Antoine Veldhoven, Sjozèf van Baal, et al.. (2005). CoPub Mapper: mining MEDLINE based on search term co-publication. BMC Bioinformatics. 6(1). 51–51. 58 indexed citations
11.
Heuvel, Edwin R. van den, Geert Geeven, Susanne Bauerschmidt, & Jan Polman. (2005). Evaluation of an Affymetrix High‐density Oligonucleotide Microarray Platform as a Measurement System. Quality and Reliability Engineering International. 21(5). 491–508. 1 indexed citations
12.
Horcajadas, J.A., A. Riesewijk, Jan Polman, et al.. (2004). Effect of controlled ovarian hyperstimulation in IVF on endometrial gene expression profiles. Molecular Human Reproduction. 11(3). 195–205. 227 indexed citations
13.
Horcajadas, J.A., A. Riesewijk, Jan Polman, et al.. (2004). Impact of controlled ovarian hyperstimulation on endometrial gene expression profiles during the window of implantation. Fertility and Sterility. 82. S92–S92. 1 indexed citations
14.
Jansen, Erik, et al.. (2004). Abnormal Gene Expression Profiles in Human Ovaries from Polycystic Ovary Syndrome Patients. Molecular Endocrinology. 18(12). 3050–3063. 136 indexed citations
15.
Mosselman, Sietse, Jan Polman, & R. Dijkema. (1996). ERβ: Identification and characterization of a novel human estrogen receptor. FEBS Letters. 392(1). 49–53. 1853 indexed citations breakdown →
16.
Duin, Marcel van, Jan Polman, H. Bunschoten, et al.. (1994). Recombinant Human Zona Pellucida Protein ZP3 Produced by Chinese Hamster Ovary Cells Induces the Human Sperm Acrosome Reaction and Promotes Sperm-Egg Fusion. Biology of Reproduction. 51(4). 607–617. 133 indexed citations
17.

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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