Frits Daeyaert

1.4k total citations
41 papers, 727 citations indexed

About

Frits Daeyaert is a scholar working on Spectroscopy, Molecular Biology and Inorganic Chemistry. According to data from OpenAlex, Frits Daeyaert has authored 41 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Spectroscopy, 13 papers in Molecular Biology and 13 papers in Inorganic Chemistry. Recurrent topics in Frits Daeyaert's work include Zeolite Catalysis and Synthesis (11 papers), Analytical Chemistry and Chromatography (8 papers) and Computational Drug Discovery Methods (8 papers). Frits Daeyaert is often cited by papers focused on Zeolite Catalysis and Synthesis (11 papers), Analytical Chemistry and Chromatography (8 papers) and Computational Drug Discovery Methods (8 papers). Frits Daeyaert collaborates with scholars based in United States, Belgium and China. Frits Daeyaert's co-authors include Michael W. Deem, Ramdas S. Pophale, Paul Lewi, Marc R. de Jonge, Jan Heeres, Paul A. J. Janssen, J. R. Durig, Benjamin J. van der Veken, H. Maarten Vinkers and D.L. Massart and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Chemical Society Reviews and Journal of Materials Chemistry A.

In The Last Decade

Frits Daeyaert

40 papers receiving 701 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frits Daeyaert United States 16 216 195 185 103 99 41 727
Guanyu Wang China 16 110 0.5× 188 1.0× 83 0.4× 226 2.2× 83 0.8× 50 708
R. Amutha India 16 39 0.2× 297 1.5× 287 1.6× 103 1.0× 38 0.4× 70 835
Alexander Fässler Switzerland 11 112 0.5× 339 1.7× 135 0.7× 103 1.0× 17 0.2× 17 559
Bethany Halford United States 12 31 0.1× 161 0.8× 94 0.5× 149 1.4× 67 0.7× 190 622
H. Maarten Vinkers Belgium 7 20 0.1× 136 0.7× 50 0.3× 51 0.5× 169 1.7× 9 307
Dapeng Li China 16 68 0.3× 213 1.1× 125 0.7× 29 0.3× 11 0.1× 48 662
Vincent Blay United States 15 279 1.3× 260 1.3× 313 1.7× 75 0.7× 142 1.4× 47 1.1k
Liangxu Xie China 13 34 0.2× 207 1.1× 144 0.8× 92 0.9× 94 0.9× 44 501
Vandana Purohit United States 9 22 0.1× 329 1.7× 87 0.5× 128 1.2× 24 0.2× 10 676
Guoning Zhang China 18 33 0.2× 203 1.0× 82 0.4× 296 2.9× 54 0.5× 80 739

Countries citing papers authored by Frits Daeyaert

Since Specialization
Citations

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

Fields of papers citing papers by Frits Daeyaert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frits Daeyaert

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

All Works

20 of 20 papers shown
1.
Tang, Xiaomin, Ömer Faruk Altundal, Frits Daeyaert, Zhiqiang Liu, & Germán Sastre. (2025). Computational insights on the role of structure-directing agents (SDAs) in the synthesis of zeolites. Chemical Society Reviews. 54(15). 7067–7092. 1 indexed citations
2.
Daeyaert, Frits, et al.. (2019). Machine-learning approach to the design of OSDAs for zeolite beta. Proceedings of the National Academy of Sciences. 116(9). 3413–3418. 58 indexed citations
3.
Daeyaert, Frits & Michael W. Deem. (2019). Design of Organic Structure Directing Agents for Chiral Zeolite Beta A. ChemistrySelect. 4(12). 3531–3537. 4 indexed citations
4.
Daeyaert, Frits & Michael W. Deem. (2018). In silico design of chiral dimers to direct the synthesis of a chiral zeolite. Molecular Physics. 116(21-22). 2836–2855. 10 indexed citations
5.
Schmidt, Joel E., Michael W. Deem, Frits Daeyaert, et al.. (2017). Enantiomerically enriched, polycrystalline molecular sieves. Proceedings of the National Academy of Sciences. 114(20). 5101–5106. 2 indexed citations
6.
Tsimafeyeu, Ilya, Frits Daeyaert, Jean‐Baptiste Joos, et al.. (2016). Molecular Modeling, de novo Design and Synthesis of a Novel, Extracellular Binding Fibroblast Growth Factor Receptor 2 Inhibitor Alofanib (RPT835). Medicinal Chemistry. 12(4). 303–317. 8 indexed citations
7.
Tsimafeyeu, Ilya, John Ludes-Meyers, Е. В. Степанова, et al.. (2016). Targeting FGFR2 with alofanib (RPT835) shows potent activity in tumour models. European Journal of Cancer. 61. 20–28. 33 indexed citations
8.
Tyulyandina, Alexandra, Wei Yin, Е. В. Степанова, et al.. (2016). Alofanib, an allosteric FGFR2 inhibitor, has potent effects on ovarian cancer growth in preclinical studies. Investigational New Drugs. 35(2). 127–133. 20 indexed citations
9.
Daeyaert, Frits, et al.. (2007). An ant algorithm for the conformational analysis of flexible molecules. Journal of Computational Chemistry. 28(5). 890–898. 12 indexed citations
10.
Jonge, Marc R. de, H. Maarten Vinkers, Joop H. van Lenthe, et al.. (2007). Ab Initio potential grid based docking: From High Performance Computing to In Silico Screening. AIP conference proceedings. 940. 168–178. 3 indexed citations
11.
Daszykowski, M., I. Stanimirova, Beata Walczak, et al.. (2005). Improving QSAR models for the biological activity of HIV Reverse Transcriptase inhibitors: Aspects of outlier detection and uninformative variable elimination. Talanta. 68(1). 54–60. 19 indexed citations
12.
Jonge, Marc R. de, Lucien M. H. Koymans, H. Maarten Vinkers, et al.. (2005). Structure Based Activity Prediction of HIV-1 Reverse Transcriptase Inhibitors. Journal of Medicinal Chemistry. 48(6). 2176–2183. 23 indexed citations
13.
Daeyaert, Frits, Marc R. de Jonge, Jan Heeres, et al.. (2005). Pareto optimal flexible alignment of molecules using a non-dominated sorting genetic algorithm. Chemometrics and Intelligent Laboratory Systems. 77(1-2). 232–237. 3 indexed citations
14.
Xu, Qingsong, Frits Daeyaert, Paul Lewi, & D.L. Massart. (2005). Studies of relationship between biological activities and HIV Reverse Transcriptase Inhibitors by Multivariate Adaptive Regression Splines with Curds and Whey. Chemometrics and Intelligent Laboratory Systems. 82(1-2). 24–30. 9 indexed citations
15.
Daeyaert, Frits, Marc R. de Jonge, Jan Heeres, et al.. (2003). A pharmacophore docking algorithm and its application to the cross‐docking of 18 HIV‐NNRTI's in their binding pockets. Proteins Structure Function and Bioinformatics. 54(3). 526–533. 22 indexed citations
16.
17.
Daeyaert, Frits, Henri Moereels, & Paul Lewi. (1998). Classification and identification of proteins by means of common and specific amino acid n-tuples in unaligned sequences. Computer Methods and Programs in Biomedicine. 56(3). 221–233. 13 indexed citations
18.
19.
Moereels, Henri, Paul Lewi, Frits Daeyaert, Emanuel Schenck, & Patricia A. Janssen. (1997). The alpha and omega of G-protein coupled receptors: a novel method for classification. Part 2. Bin classification.. PubMed. 5(3-4). 139–48. 3 indexed citations
20.

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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