Herman van Vlijmen

5.9k total citations · 1 hit paper
98 papers, 4.3k citations indexed

About

Herman van Vlijmen is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Herman van Vlijmen has authored 98 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Molecular Biology, 34 papers in Computational Theory and Mathematics and 14 papers in Organic Chemistry. Recurrent topics in Herman van Vlijmen's work include Computational Drug Discovery Methods (34 papers), Protein Structure and Dynamics (20 papers) and Receptor Mechanisms and Signaling (17 papers). Herman van Vlijmen is often cited by papers focused on Computational Drug Discovery Methods (34 papers), Protein Structure and Dynamics (20 papers) and Receptor Mechanisms and Signaling (17 papers). Herman van Vlijmen collaborates with scholars based in Belgium, United States and Netherlands. Herman van Vlijmen's co-authors include Martin Karplus, Yuan Feng, Andrej Săli, Adriaan P. IJzerman, Gerard J. P. van Westen, Gary Tresadern, Laura Pérez‐Benito, Martin Karplus, Jörg K. Wegner and Eelke B. Lenselink and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Chemical Physics.

In The Last Decade

Herman van Vlijmen

95 papers receiving 4.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Evaluation of comparative protein modeling by MODELLER

1995 930 citations Andrej Săli, Yuan Feng et al. Proteins Structure Function and Bioinformatics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Herman van Vlijmen Belgium	38	3.1k	1.3k	784	406	377	98	4.3k
Paul Czodrowski Germany	21	2.5k 0.8×	1.3k 1.0×	738 0.9×	318 0.8×	242 0.6×	41	4.2k
Christine Zardecki United States	18	3.2k 1.0×	897 0.7×	778 1.0×	414 1.0×	184 0.5×	45	4.5k
Daniel Seeliger Germany	24	2.5k 0.8×	798 0.6×	475 0.6×	386 1.0×	318 0.8×	43	3.8k
Gennady M. Verkhivker United States	39	3.7k 1.2×	1.8k 1.4×	746 1.0×	382 0.9×	407 1.1×	169	4.8k
David W. Ritchie France	26	2.5k 0.8×	907 0.7×	726 0.9×	328 0.8×	216 0.6×	70	3.6k
Shuanghong Huo United States	21	4.0k 1.3×	1.1k 0.8×	712 0.9×	611 1.5×	343 0.9×	42	5.5k
Sheng‐You Huang China	34	4.3k 1.4×	1.8k 1.4×	848 1.1×	385 0.9×	359 1.0×	116	6.0k
Romelia Salomón–Ferrer United States	11	3.7k 1.2×	690 0.5×	900 1.1×	495 1.2×	242 0.6×	17	5.3k
Claudio N. Cavasotto United States	37	2.7k 0.9×	1.8k 1.3×	431 0.5×	576 1.4×	283 0.8×	85	4.2k
Jacob D. Durrant United States	33	2.9k 0.9×	1.7k 1.3×	666 0.8×	487 1.2×	188 0.5×	78	4.2k

Countries citing papers authored by Herman van Vlijmen

Since Specialization

Citations

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

Fields of papers citing papers by Herman van Vlijmen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Herman van Vlijmen

This figure shows the co-authorship network connecting the top 25 collaborators of Herman van Vlijmen. A scholar is included among the top collaborators of Herman van Vlijmen 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 Herman van Vlijmen. Herman van Vlijmen 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

Khalil, Basem A., Leo Price, Natalia Dyubankova, et al.. (2025). A Patient‐Derived 3D Cyst Model of Polycystic Kidney Disease That Mimics Disease Development and Responds to Repurposing Candidates. Clinical and Translational Science. 18(4). e70214–e70214.

Khalil, Basem A., et al.. (2025). Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling. Journal of Chemical Information and Modeling. 65(24). 13057–13069.

Carbajo, Rodrigo J., Edgar Jacoby, Yanting Yin, et al.. (2024). Structure–Activity Relationship of Oxacyclo- and Triazolo-Containing Respiratory Syncytial Virus Polymerase Inhibitors. ACS Medicinal Chemistry Letters. 15(9). 1549–1558. 2 indexed citations

Matricon, Pierre, Jérôme Hénin, Grace Brannigan, et al.. (2023). Alchemical Free Energy Calculations on Membrane-Associated Proteins. Journal of Chemical Theory and Computation. 19(21). 7437–7458. 13 indexed citations

Liu, Xuhan, Kai Ye, Herman van Vlijmen, Adriaan P. IJzerman, & Gerard J. P. van Westen. (2023). DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learning. Journal of Cheminformatics. 15(1). 24–24. 45 indexed citations

Berthelot, Didier, Stefan Pype, Herman van Vlijmen, et al.. (2023). Kinetic profiling of novel spirobenzo-oxazinepiperidinone derivatives as equilibrative nucleoside transporter 1 inhibitors. Purinergic Signalling. 20(2). 193–205. 3 indexed citations

Tresadern, Gary, et al.. (2021). Mechanism of covalent binding of ibrutinib to Bruton's tyrosine kinase revealed by QM/MM calculations. Chemical Science. 12(15). 5511–5516. 34 indexed citations

Buyck, Christophe, Bing Qi, Herman van Vlijmen, et al.. (2021). Identification of novel inhibitors of rat Mrp3. European Journal of Pharmaceutical Sciences. 162. 105813–105813. 2 indexed citations

Vlijmen, Herman van, et al.. (2021). The European Lead Factory: An updated HTS compound library for innovative drug discovery. Drug Discovery Today. 26(10). 2406–2413. 11 indexed citations

10.

Sydow, Dominique, Angelika Szengel, Herman van Vlijmen, et al.. (2019). Advances and Challenges in Computational Target Prediction. Journal of Chemical Information and Modeling. 59(5). 1728–1742. 77 indexed citations

11.

Gouka, Robin J., et al.. (2019). Identification of novel small molecule inhibitors for solute carrier SGLT1 using proteochemometric modeling. Journal of Cheminformatics. 11(1). 15–15. 20 indexed citations

12.

Tresadern, Gary, Andrés A. Trabanco, Laura Pérez‐Benito, et al.. (2017). Identification of Allosteric Modulators of Metabotropic Glutamate 7 Receptor Using Proteochemometric Modeling. Journal of Chemical Information and Modeling. 57(12). 2976–2985. 15 indexed citations

13.

Keränen, Henrik, Laura Pérez‐Benito, Francisca Delgado, et al.. (2017). Acylguanidine Beta Secretase 1 Inhibitors: A Combined Experimental and Free Energy Perturbation Study. Journal of Chemical Theory and Computation. 13(3). 1439–1453. 63 indexed citations

14.

Sherborne, Bradley, Veerabahu Shanmugasundaram, Alan C. Cheng, et al.. (2016). Collaborating to improve the use of free-energy and other quantitative methods in drug discovery. Journal of Computer-Aided Molecular Design. 30(12). 1139–1141. 38 indexed citations

15.

Jones, Philip S., et al.. (2015). The ELF Honest Data Broker: informatics enabling public–private collaboration in a precompetitive arena. Drug Discovery Today. 21(1). 97–102. 18 indexed citations

16.

Borght, Koen Van der, Geert Verbeke, & Herman van Vlijmen. (2014). Multi-model inference using mixed effects from a linear regression based genetic algorithm. BMC Bioinformatics. 15(1). 88–88. 4 indexed citations

17.

Lin, Edward Yin-Shiang, Kevin M. Guckian, Laura Silvian, et al.. (2008). Structure–activity relationship of ortho- and meta-phenol based LFA-1 ICAM inhibitors. Bioorganic & Medicinal Chemistry Letters. 18(19). 5245–5248. 3 indexed citations

18.

Clark, Louis A., et al.. (2006). Trends in Antibody Sequence Changes during the Somatic Hypermutation Process. The Journal of Immunology. 177(1). 333–340. 69 indexed citations

19.

Belville, Corinne, Herman van Vlijmen, Christian W. Ehrenfels, et al.. (2003). Mutations of the Anti-Mullerian Hormone Gene in Patients with Persistent Mullerian Duct Syndrome: Biosynthesis, Secretion, and Processing of the Abnormal Proteins and Analysis Using a Three-Dimensional Model. Molecular Endocrinology. 18(3). 708–721. 65 indexed citations

20.

Săli, Andrej, et al.. (1995). Evaluation of comparative protein modeling by MODELLER. Proteins Structure Function and Bioinformatics. 23(3). 318–326. 930 indexed citations breakdown →

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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