Lies Bogaert

751 total citations
13 papers, 533 citations indexed

About

Lies Bogaert is a scholar working on Epidemiology, Infectious Diseases and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Lies Bogaert has authored 13 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Epidemiology, 4 papers in Infectious Diseases and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Lies Bogaert's work include Viral gastroenteritis research and epidemiology (3 papers), Virus-based gene therapy research (3 papers) and Respiratory viral infections research (3 papers). Lies Bogaert is often cited by papers focused on Viral gastroenteritis research and epidemiology (3 papers), Virus-based gene therapy research (3 papers) and Respiratory viral infections research (3 papers). Lies Bogaert collaborates with scholars based in Belgium, United States and Netherlands. Lies Bogaert's co-authors include Roland Zahn, Ann Martens, Hanneke Schuitemaker, Myra N. Widjojoatmodjo, Daphné Truan, Johannes P. M. Langedijk, Pascale Bouchier, Anders Krarup, Jason S. McLellan and Cindy De Baere and has published in prestigious journals such as Nature Communications, Cancer Research and Journal of General Virology.

In The Last Decade

Lies Bogaert

13 papers receiving 514 citations

Peers

Lies Bogaert
Andrea Minola Switzerland
Shona MacRae United Kingdom
Bo Chi United States
Matthew R. Murawski United States
Andrés Chang United States
Deborah Moore United States
Carla D. Pretto United States
Andrea Minola Switzerland
Lies Bogaert
Citations per year, relative to Lies Bogaert Lies Bogaert (= 1×) peers Andrea Minola

Countries citing papers authored by Lies Bogaert

Since Specialization
Citations

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

Fields of papers citing papers by Lies Bogaert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lies Bogaert

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

All Works

13 of 13 papers shown
1.
Silva, Diane M. Da, et al.. (2022). Investigation of the Optimal Prime Boost Spacing Regimen for a Cancer Therapeutic Vaccine Targeting Human Papillomavirus. Cancers. 14(17). 4339–4339. 3 indexed citations
2.
Bockstal, Viki, et al.. (2018). A comparative study between outbred and inbred rat strains for the use in in vivo IPV potency testing. Vaccine. 36(21). 2917–2920. 3 indexed citations
3.
Bogaert, Lies, Patrick Wanningen, Katarina Radošević, et al.. (2016). Recombinant measles virus incorporating heterologous viral membrane proteins for use as vaccines. Journal of General Virology. 97(9). 2117–2128. 9 indexed citations
4.
Krarup, Anders, Daphné Truan, Lies Bogaert, et al.. (2015). A highly stable prefusion RSV F vaccine derived from structural analysis of the fusion mechanism. Nature Communications. 6(1). 8143–8143. 258 indexed citations
6.
Bogaert, Lies, Andrew W. Woodham, Diane M. Da Silva, et al.. (2015). A novel murine model for evaluating bovine papillomavirus prophylactics/therapeutics for equine sarcoid-like tumours. Journal of General Virology. 96(9). 2764–2768. 2 indexed citations
7.
Bogaert, Lies, Anouk Willemsen, María Alma Bracho, et al.. (2012). EcPV2 DNA in equine genital squamous cell carcinomas and normal genital mucosa. Veterinary Microbiology. 158(1-2). 33–41. 43 indexed citations
8.
Bogaert, Lies, Ann Martens, W. Martin Kast, Eric Van Marck, & H. De Cock. (2010). Bovine papillomavirus DNA can be detected in keratinocytes of equine sarcoid tumors. Veterinary Microbiology. 146(3-4). 269–275. 45 indexed citations
9.
Kanodia, Shreya, et al.. (2010). Expression of LIGHT/TNFSF14 Combined with Vaccination against Human Papillomavirus Type 16 E7 Induces Significant Tumor Regression. Cancer Research. 70(10). 3955–3964. 38 indexed citations
10.
Martens, Ann, et al.. (2009). Distal limb cast sores in horses: risk factors and early detection using thermography. Ghent University Academic Bibliography (Ghent University). 1 indexed citations
11.
Martens, Ann, et al.. (2008). Osteochondral Fragmentation in the Synovial Pad of the Fetlock in Warmblood Horses. Veterinary Surgery. 37(7). 613–618. 8 indexed citations
12.
Martens, Ann, et al.. (2008). Lower limb cast sores in horses: risk factors and early detection using thermography.. Ghent University Academic Bibliography (Ghent University). 108–110. 1 indexed citations
13.
Bogaert, Lies, Mario Van Poucke, Cindy De Baere, et al.. (2006). Selection of a set of reliable reference genes for quantitative real-time PCR in normal equine skin and in equine sarcoids. BMC Biotechnology. 6(1). 24–24. 76 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026