Jan Maes

22 papers receiving 784 citations

Peers

Jan Maes
Comparison fields: 5 of 115
  • Cell Biology 214
  • Complementary and alternative medicine 59
  • Infectious Diseases 110
  • Health, Toxicology and Mutagenesis 77
  • Immunology 106
Replace Alphonse Calenda with:
Alphonse Calenda France
Charles V. Lowry United States
Rong He China
Ying‐Hua Zhang China
Jing‐Fei Huang China
Sabina Muend United States
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Ting Cao China
In Soon Choi South Korea
Yusuke Sato Japan
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Citations per year

Countries citing papers authored by Jan Maes

Since Specialization
Citations

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

Fields of papers citing papers by Jan Maes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Maes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Maes Line = papers co-authored together Jan Maes links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012188
2 2019123
3 2012104
4 201791
5 201376
6 201166
7 201349
8 201725
9 200418
10
In vitro accumulation and permeation of hypericin and lipophilic analogues in 2-D and 3-D cellular systems.
200712
11 202111
12 201710
13 20077
14 20005
15 20075
16 20214
17
Compactly supported Powell-Sabin spline multiwavelets in Sobolev spaces
20053
18 20091
19 20241
20 20101

About Jan Maes

Jan Maes is a scholar working on Molecular Biology, Cell Biology, Computational Mechanics, Computer Vision and Pattern Recognition and Genetics, having authored 23 papers that have together received 802 indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (5 papers), Image and Signal Denoising Methods (4 papers), Advanced Numerical Analysis Techniques (4 papers), Natural product bioactivities and synthesis (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Reproductive biology and impacts on aquatic species (2 papers), Biological and pharmacological studies of plants (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Cell Biology (214 citations), Complementary and alternative medicine (59 citations), Infectious Diseases (110 citations), Health, Toxicology and Mutagenesis (77 citations) and Immunology (106 citations). Jan Maes has collaborated with scholars based in Belgium, Tanzania and Ecuador. Frequent co-authors include Peter de Witte, Camila V. Esguerra, Alexander D. Crawford, Olivia Erin M Buenafe, Adriana Orellana-Paucar, Wim M. De Borggraeve, Appolinary R. Kamuhabwa, Annelii Ny, Sebastian Munck and Adhemar Bultheel. Their work appears in journals such as PLoS ONE, Planta Medica, ACS Chemical Neuroscience, Journal of materials research/Pratt's guide to venture capital sources and Environmental Science and Pollution Research.

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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