Denis van Beurden

1.0k total citations
18 papers, 795 citations indexed

About

Denis van Beurden is a scholar working on Physiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Denis van Beurden has authored 18 papers receiving a total of 795 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Physiology, 4 papers in Molecular Biology and 4 papers in Cell Biology. Recurrent topics in Denis van Beurden's work include Adipose Tissue and Metabolism (11 papers), Muscle metabolism and nutrition (4 papers) and Diet and metabolism studies (4 papers). Denis van Beurden is often cited by papers focused on Adipose Tissue and Metabolism (11 papers), Muscle metabolism and nutrition (4 papers) and Diet and metabolism studies (4 papers). Denis van Beurden collaborates with scholars based in Netherlands, Spain and Sweden. Denis van Beurden's co-authors include Patrick Schrauwen, Inge Huitinga, Dick F. Swaab, Matthijs K. C. Hesselink, Zeynel A. Erkut, Joris Hoeks, Silvie Timmers, Gert Schaart, Esther Moonen‐Kornips and Madeleen Bosma and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and PLoS ONE.

In The Last Decade

Denis van Beurden

18 papers receiving 787 citations

Peers

Denis van Beurden
Jaroslav Pavel United States
Hyunbae Kim United States
Serge Summermatter Switzerland
Matthew R. Sapio United States
Chang Woo Chae South Korea
Jaroslav Pavel United States
Denis van Beurden
Citations per year, relative to Denis van Beurden Denis van Beurden (= 1×) peers Jaroslav Pavel

Countries citing papers authored by Denis van Beurden

Since Specialization
Citations

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

Fields of papers citing papers by Denis van Beurden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Denis van Beurden. 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 Denis van Beurden. The network helps show where Denis van Beurden may publish in the future.

Co-authorship network of co-authors of Denis van Beurden

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

All Works

18 of 18 papers shown
1.
Camarero‐Espinosa, Sandra, Liu Hong, Denis van Beurden, et al.. (2024). 3D Niche‐Inspired Scaffolds as a Stem Cell Delivery System for the Regeneration of the Osteochondral Interface. Advanced Materials. 36(34). e2310258–e2310258. 19 indexed citations
2.
Rho, Hoon Suk, et al.. (2023). Direct deep UV lithography to micropattern PMMA for stem cell culture. Materials Today Bio. 22. 100779–100779. 6 indexed citations
3.
Vermeulen, Steven, Kèvin Knoops, Hans Duimel, et al.. (2023). An in vitro model system based on calcium- and phosphate ion-induced hMSC spheroid mineralization. Materials Today Bio. 23. 100844–100844. 10 indexed citations
4.
Tullemans, Bibian M. E., et al.. (2021). Characterization of Atherosclerotic Plaque Coating for Thrombosis Microfluidics Assays. Cellular and Molecular Bioengineering. 15(1). 55–65. 6 indexed citations
5.
Bosma, Madeleen, Matthijs K. C. Hesselink, Lauren M. Sparks, et al.. (2012). Perilipin 2 Improves Insulin Sensitivity in Skeletal Muscle Despite Elevated Intramuscular Lipid Levels. Diabetes. 61(11). 2679–2690. 123 indexed citations
6.
Paglialunga, Sabina, Madeleen Bosma, M. Pilar Valdecantos, et al.. (2012). Targeting of mitochondrial reactive oxygen species production does not avert lipid-induced insulin resistance in muscle tissue from mice. Diabetologia. 55(10). 2759–2768. 32 indexed citations
7.
Timmers, Silvie, Miranda Nabben, Madeleen Bosma, et al.. (2012). Augmenting muscle diacylglycerol and triacylglycerol content by blocking fatty acid oxidation does not impede insulin sensitivity. Proceedings of the National Academy of Sciences. 109(29). 11711–11716. 64 indexed citations
8.
Nabben, Miranda, Irina G. Shabalina, Esther Moonen‐Kornips, et al.. (2011). Uncoupled respiration, ROS production, acute lipotoxicity and oxidative damage in isolated skeletal muscle mitochondria from UCP3-ablated mice. Biochimica et Biophysica Acta (BBA) - Bioenergetics. 1807(9). 1095–1105. 34 indexed citations
9.
Timmers, Silvie, Johan de Vogel‐van den Bosch, Matthijs K. C. Hesselink, et al.. (2011). Paradoxical Increase in TAG and DAG Content Parallel the Insulin Sensitizing Effect of Unilateral DGAT1 Overexpression in Rat Skeletal Muscle. PLoS ONE. 6(1). e14503–e14503. 39 indexed citations
10.
Timmers, Silvie, Johan de Vogel‐van den Bosch, N. de Wit, et al.. (2011). Differential effects of saturated versus unsaturated dietary fatty acids on weight gain and myocellular lipid profiles in mice. Nutrition and Diabetes. 1(7). e11–e11. 30 indexed citations
11.
Nabben, Miranda, Joris Hoeks, Esther Moonen‐Kornips, et al.. (2011). Significance of uncoupling protein 3 in mitochondrial function upon mid- and long-term dietary high-fat exposure. FEBS Letters. 585(24). 4010–4017. 17 indexed citations
12.
Bosch, Johan de Vogel‐van den, Joris Hoeks, Silvie Timmers, et al.. (2010). The Effects of Long‐ or Medium‐Chain Fat Diets on Glucose Tolerance and Myocellular Content of Lipid Intermediates in Rats. Obesity. 19(4). 792–799. 18 indexed citations
13.
Bosch, Johan de Vogel‐van den, Sjoerd A.A. van den Berg, Silvia Bijland, et al.. (2010). High-fat diets rich in medium- versus long-chain fatty acids induce distinct patterns of tissue specific insulin resistance. The Journal of Nutritional Biochemistry. 22(4). 366–371. 23 indexed citations
14.
Hommelberg, Pascal P. H., Jogchum Plat, Lauren M. Sparks, et al.. (2010). Palmitate-induced skeletal muscle insulin resistance does not require NF-κB activation. Cellular and Molecular Life Sciences. 68(7). 1215–1225. 24 indexed citations
15.
Hoeks, Joris, Noud A. van Herpen, Marco Mensink, et al.. (2010). Prolonged Fasting Identifies Skeletal Muscle Mitochondrial Dysfunction as Consequence Rather Than Cause of Human Insulin Resistance. Diabetes. 59(9). 2117–2125. 120 indexed citations
16.
Ishunina, Tatjana A., Denis van Beurden, Unga A. Unmehopa, et al.. (2004). Diminished aromatase immunoreactivity in the hypothalamus, but not in the basal forebrain nuclei in Alzheimer’s disease. Neurobiology of Aging. 26(2). 173–194. 80 indexed citations
17.
Huitinga, Inge, Zeynel A. Erkut, Denis van Beurden, & Dick F. Swaab. (2003). The Hypothalamo‐Pituitary‐Adrenal Axis in Multiple Sclerosis. Annals of the New York Academy of Sciences. 992(1). 118–128. 52 indexed citations
18.
Huitinga, Inge, Zeynel A. Erkut, Denis van Beurden, & Dick F. Swaab. (2003). Impaired hypothalamus‐pituitary‐adrenal axis activity and more severe multiple sclerosis with hypothalamic lesions. Annals of Neurology. 55(1). 37–45. 98 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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