M. J. E. Wassenaar

23 total papers · 1.1k total citations
18 papers, 800 citations indexed

About

M. J. E. Wassenaar is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, M. J. E. Wassenaar has authored 18 papers receiving a total of 800 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Molecular Biology and 4 papers in Pathology and Forensic Medicine. Recurrent topics in M. J. E. Wassenaar's work include Pituitary Gland Disorders and Treatments (12 papers), Growth Hormone and Insulin-like Growth Factors (8 papers) and TGF-β signaling in diseases (4 papers). M. J. E. Wassenaar is often cited by papers focused on Pituitary Gland Disorders and Treatments (12 papers), Growth Hormone and Insulin-like Growth Factors (8 papers) and TGF-β signaling in diseases (4 papers). M. J. E. Wassenaar collaborates with scholars based in Netherlands. M. J. E. Wassenaar's co-authors include Nienke R. Biermasz, Alberto M. Pereira, Johannes A. Romijn, Johannes W. A. Smit, Ferdinand Roelfsema, Nieke E Kokshoorn, Jitske Tiemensma, M. Kloppenburg, Herman M. Kroon and Huub A. M. Middelkoop and has published in prestigious journals such as Endocrine Reviews, The Journal of Clinical Endocrinology & Metabolism and Endocrinology.

In The Last Decade

M. J. E. Wassenaar

17 papers receiving 785 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
M. J. E. Wassenaar	697	142	136	94	81	18	800
C. Wang	468 0.7×	99 0.7×	116 0.9×	176 1.9×	96 1.2×	23	816
G. K. Stalla	438 0.6×	53 0.4×	130 1.0×	79 0.8×	54 0.7×	27	772
Donald A. Holub	548 0.8×	52 0.4×	142 1.0×	144 1.5×	95 1.2×	21	983
Harvey Cushing	482 0.7×	57 0.4×	219 1.6×	108 1.1×	47 0.6×	13	804
S. Lederbogen	559 0.8×	327 2.3×	160 1.2×	52 0.6×	69 0.9×	17	765
Ingrid Ernest	621 0.9×	47 0.3×	211 1.6×	148 1.6×	85 1.0×	17	824
Chantal Daumerie	819 1.2×	116 0.8×	122 0.9×	84 0.9×	68 0.8×	32	1.0k
Carol Stolarski	453 0.6×	216 1.5×	153 1.1×	197 2.1×	27 0.3×	26	766
Mirella Hage	504 0.7×	55 0.4×	181 1.3×	145 1.5×	124 1.5×	30	961
Peter Eng	591 0.8×	210 1.5×	158 1.2×	138 1.5×	39 0.5×	28	1.0k

Countries citing papers authored by M. J. E. Wassenaar

Since Specialization

Citations

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

Fields of papers citing papers by M. J. E. Wassenaar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. J. E. Wassenaar. 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 M. J. E. Wassenaar. The network helps show where M. J. E. Wassenaar may publish in the future.

Co-authorship network of co-authors of M. J. E. Wassenaar

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

All Works

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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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