Marian Beekman

31.7k total citations
125 papers, 4.5k citations indexed

About

Marian Beekman is a scholar working on Molecular Biology, Physiology and Aging. According to data from OpenAlex, Marian Beekman has authored 125 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 43 papers in Physiology and 32 papers in Aging. Recurrent topics in Marian Beekman's work include Genetics, Aging, and Longevity in Model Organisms (32 papers), Birth, Development, and Health (27 papers) and Diet and metabolism studies (25 papers). Marian Beekman is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (32 papers), Birth, Development, and Health (27 papers) and Diet and metabolism studies (25 papers). Marian Beekman collaborates with scholars based in Netherlands, Germany and United Kingdom. Marian Beekman's co-authors include P. Eline Slagboom, Rudi G. J. Westendorp, Diana van Heemst, Jeanine J. Houwing‐Duistermaat, Anton J.M. de Craen, Bastiaan T. Heijmans, Simon P. Mooijaart, Gerard J. Blauw, Joris Deelen and Hae‐Won Uh and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The EMBO Journal.

In The Last Decade

Marian Beekman

119 papers receiving 4.4k citations

Peers

Marian Beekman

PHYSI

AGING

GENET

PPCH

Annibale Alessandro Puca Italy

Michał M. Masternak United States

Felipe Sierra United States

Michael B. Stout United States

Ling Zhao China

Manlio Vinciguerra Italy

Susan N. Perkins United States

Clinton M. Astle United States

Gianluigi Mazzoccoli Italy

Björn Schumacher Germany

Annibale Alessandro Puca Italy

Marian Beekman

2.2k ×1.3

1.2k ×0.9

PHYSI

1.2k ×1.1

AGING

627 ×0.9

GENET

458 ×0.8

PPCH

Citations per year, relative to Marian Beekman Marian Beekman (= 1×) peers Annibale Alessandro Puca

Countries citing papers authored by Marian Beekman

Since Specialization

Citations

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

Fields of papers citing papers by Marian Beekman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marian Beekman

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

All Works

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20 of 20 papers shown

Kat, Annelien C. de, et al.. (2024). Late reproduction is associated with extended female survival but not with familial longevity. Reproductive BioMedicine Online. 49(3). 104073–104073.

Mooijaart, Simon P., Floor J. van Deudekom, Dina Vojinović, et al.. (2024). The performance of metabolomics-based prediction scores for mortality in older patients with solid tumors. GeroScience. 46(6). 5615–5627. 3 indexed citations

Polinder‐Bos, Harmke A., Daniele Bizzarri, Dina Vojinović, et al.. (2023). Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk. The Journals of Gerontology Series A. 78(10). 1753–1762. 39 indexed citations

Bizzarri, Daniele, et al.. (2023). Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health’s 1H-NMR Metabolomics Platform. Metabolites. 13(12). 1181–1181. 9 indexed citations

Giannos, Panagiotis, et al.. (2022). Gut microbiome changes due to sleep disruption in older and younger individuals: a case for sarcopenia?. SLEEP. 45(12). 17 indexed citations

Bizzarri, Daniele, Marcel Reinders, Marian Beekman, P. Eline Slagboom, & Erik B. van den Akker. (2022). MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health’s 1H-NMR metabolomics data. Bioinformatics. 38(15). 3847–3849. 11 indexed citations

Gehrmann, Thies, Marian Beekman, Erik B. van den Akker, et al.. (2022). PLIS : A metabolomic response monitor to a lifestyle intervention study in older adults. The FASEB Journal. 36(11). e22578–e22578. 8 indexed citations

Berg, Niels van den, et al.. (2021). Improved selection of participants in genetic longevity studies: family scores revisited. BMC Medical Research Methodology. 21(1). 7–7.

Wang, Wenyi, Ko Willems van Dijk, Carolien A. Wijsman, et al.. (2021). Differential insulin sensitivity of NMR-based metabolomic measures in a two-step hyperinsulinemic euglycemic clamp study. Metabolomics. 17(6). 57–57.

10.

Bizzarri, Daniele, et al.. (2021). 1H-NMR metabolomics-based surrogates to impute common clinical risk factors and endpoints. EBioMedicine. 75. 103764–103764. 16 indexed citations

11.

Berg, Niels van den, Mar Rodríguez‐Girondo, Kees Mandemakers, et al.. (2020). Longevity Relatives Count score identifies heritable longevity carriers and suggests case improvement in genetic studies. Aging Cell. 19(6). e13139–e13139. 11 indexed citations

12.

Benedetti, Elisa, Maja Pučić‐Baković, Toma Keser, et al.. (2020). Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference. Metabolites. 10(7). 271–271. 15 indexed citations

13.

Beekman, Marian, Erik B. van den Akker, Raymond Noordam, et al.. (2020). Lifestyle‐Intervention‐Induced Reduction of Abdominal Fat Is Reflected by a Decreased Circulating Glycerol Level and an Increased HDL Diameter. Molecular Nutrition & Food Research. 64(10). e1900818–e1900818. 7 indexed citations

14.

Surowiec, Izabella, Raymond Noordam, Kate Bennett, et al.. (2019). Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease. Metabolomics. 15(2). 23–23. 42 indexed citations

15.

Gunn, David A., et al.. (2019). Basal cell carcinoma genetic susceptibility increases the rate of skin ageing: a Mendelian randomization study. Journal of the European Academy of Dermatology and Venereology. 34(1). 97–100. 6 indexed citations

16.

Craen, A.J.M. de, et al.. (2017). Evidence of genetic enrichment for exceptional survival using a family approach: the Leiden Longevity Study (Reprinted from EUROPEAN JOURNAL OF HUMAN GENETICS, vol 13, pg 1025-1032, 2005). European Journal of Human Genetics. 25. 1 indexed citations

17.

Ramos, Y.F., Steffan D. Bos, Ruud van der Breggen, et al.. (2014). A gain of function mutation in TNFRSF11B causes osteoarthritis with chondrocalcinosis. Osteoarthritis and Cartilage. 22. S226–S226. 1 indexed citations

18.

Akker, Erik B. van den, Bas Verbruggen, B.T. Heijmans, et al.. (2011). Integrating Protein-Protein Interaction Networks with Gene- Gene Co-Expression Networks improves Gene Signatures for Classifying Breast Cancer Metastasis. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 8(2). 222–238. 16 indexed citations

19.

Heemst, Diana van, Marian Beekman, Simon P. Mooijaart, et al.. (2005). Reduced insulin/IGF‐1 signalling and human longevity. Aging Cell. 4(2). 79–85. 211 indexed citations

20.

Putter, Hein, Marian Beekman, Nico Lakenberg, et al.. (2004). Mapping QTLs for HDL-C, LDL-C and Associated Proteins and Identification of Underlying Genetic Variation: A Meta-analysis of Four Genome Scans. Twin Research and Human Genetics. 7(6). 683. 1 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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