Jörg K. Wegner

4.1k total citations · 1 hit paper
49 papers, 2.3k citations indexed

About

Jörg K. Wegner is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Jörg K. Wegner has authored 49 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computational Theory and Mathematics, 30 papers in Molecular Biology and 21 papers in Materials Chemistry. Recurrent topics in Jörg K. Wegner's work include Computational Drug Discovery Methods (39 papers), Machine Learning in Materials Science (21 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Jörg K. Wegner is often cited by papers focused on Computational Drug Discovery Methods (39 papers), Machine Learning in Materials Science (21 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Jörg K. Wegner collaborates with scholars based in Belgium, United States and Germany. Jörg K. Wegner's co-authors include Andreas Zell, Hugo Ceulemans, Sepp Hochreiter, Günter Klambauer, Holger Fröhlich, Andreas Bender, Gerard J. P. van Westen, Adriaan P. IJzerman, Herman van Vlijmen and Marvin Steijaert and has published in prestigious journals such as PLoS ONE, Scientific Reports and Communications of the ACM.

In The Last Decade

Jörg K. Wegner

47 papers receiving 2.3k 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.

Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

2018 352 citations Andreas Mayr, Günter Klambauer et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jörg K. Wegner Belgium	26	1.5k	1.4k	668	230	197	49	2.3k
Gerard J. P. van Westen Netherlands	34	1.5k 1.0×	2.1k 1.5×	442 0.7×	202 0.9×	130 0.7×	130	3.2k
Ola Spjuth Sweden	31	1.2k 0.8×	1.5k 1.0×	332 0.5×	301 1.3×	300 1.5×	125	2.9k
Francesca Grisoni Italy	32	1.8k 1.2×	1.5k 1.0×	939 1.4×	179 0.8×	213 1.1×	89	3.3k
Thomas Blaschke Germany	11	1.9k 1.3×	1.4k 1.0×	1.3k 1.9×	99 0.4×	227 1.2×	13	2.6k
Paul Czodrowski Germany	21	1.3k 0.8×	2.5k 1.8×	738 1.1×	144 0.6×	228 1.2×	41	4.2k
Christian Tyrchan Sweden	23	1.9k 1.3×	1.7k 1.2×	1.3k 1.9×	170 0.7×	146 0.7×	56	2.8k
Evan N. Feinberg United States	9	1.7k 1.1×	2.0k 1.4×	1.3k 2.0×	161 0.7×	306 1.6×	17	3.2k
Marcus Olivecrona Sweden	3	1.5k 1.0×	1.1k 0.8×	980 1.5×	77 0.3×	203 1.0×	3	2.1k
Djork-Arné Clevert Germany	18	1.1k 0.8×	1.5k 1.1×	765 1.1×	92 0.4×	197 1.0×	38	2.4k
Wengong Jin United States	12	2.0k 1.3×	1.6k 1.1×	1.6k 2.4×	114 0.5×	387 2.0×	24	3.6k

Countries citing papers authored by Jörg K. Wegner

Since Specialization

Citations

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

Fields of papers citing papers by Jörg K. Wegner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jörg K. Wegner. 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 Jörg K. Wegner. The network helps show where Jörg K. Wegner may publish in the future.

Co-authorship network of co-authors of Jörg K. Wegner

This figure shows the co-authorship network connecting the top 25 collaborators of Jörg K. Wegner. A scholar is included among the top collaborators of Jörg K. Wegner 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 Jörg K. Wegner. Jörg K. Wegner 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

Verhoeven, Jonas, et al.. (2025). Improving route development using convergent retrosynthesis planning. Journal of Cheminformatics. 17(1). 26–26. 2 indexed citations

Nugmanov, Ramil, et al.. (2025). Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling. Journal of Cheminformatics. 17(1). 25–25. 3 indexed citations

Sandonas, Leonardo Medrano, Dries Van Rompaey, David F. Hahn, et al.. (2024). Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules. Scientific Data. 11(1). 742–742. 17 indexed citations

Rompaey, Dries Van, Mazen Ahmad, Justin S. Cisar, et al.. (2024). Toward Dose Prediction at Point of Design. Journal of Medicinal Chemistry. 67(24). 22282–22290. 5 indexed citations

McClure, Kelly J., Jonas Verhoeven, Natalia Dyubankova, et al.. (2023). Global reactivity models are impactful in industrial synthesis applications. Journal of Cheminformatics. 15(1). 20–20. 10 indexed citations

Nugmanov, Ramil, et al.. (2022). Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task. Journal of Chemical Information and Modeling. 62(14). 3307–3315. 21 indexed citations

Seidl, Philipp, Philipp Renz, Natalia Dyubankova, et al.. (2021). Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction.. arXiv (Cornell University). 1 indexed citations

Sturm, Noé, Andreas Mayr, Vladimir Chupakhin, et al.. (2020). Industry-scale application and evaluation of deep learning for drug target prediction. Journal of Cheminformatics. 12(1). 26–26. 29 indexed citations

Cox, Michael J., Steffen Jaensch, Seong Joo Koo, et al.. (2020). Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines. Scientific Reports. 10(1). 13262–13262. 36 indexed citations

10.

Renz, Philipp, Dries Van Rompaey, Jörg K. Wegner, Sepp Hochreiter, & Günter Klambauer. (2019). On failure modes in molecule generation and optimization. Drug Discovery Today Technologies. 32-33. 55–63. 86 indexed citations

11.

Wolf, Hans, Kirsten Van Hoorde, An De Bondt, et al.. (2018). High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity. Assay and Drug Development Technologies. 16(3). 162–176. 21 indexed citations

12.

Simm, Jaak, Günter Klambauer, Ádám Arany, et al.. (2018). Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery. Cell chemical biology. 25(5). 611–618.e3. 140 indexed citations

13.

Westen, Gerard J. P. van, et al.. (2013). Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets. Journal of Cheminformatics. 5(1). 41–41. 81 indexed citations

14.

Westen, Gerard J. P. van, et al.. (2013). Significantly Improved HIV Inhibitor Efficacy Prediction Employing Proteochemometric Models Generated From Antivirogram Data. PLoS Computational Biology. 9(2). e1002899–e1002899. 39 indexed citations

15.

Horst, Eelke van der, Julio E. Peironcely, Gerard J. P. van Westen, et al.. (2011). Chemogenomics Approaches for Receptor Deorphanization and Extensions of the Chemogenomics Concept to Phenotypic Space. Current Topics in Medicinal Chemistry. 11(15). 1964–1977. 14 indexed citations

16.

Westen, Gerard J. P. van, Jörg K. Wegner, Peggy Geluykens, et al.. (2011). Which Compound to Select in Lead Optimization? Prospectively Validated Proteochemometric Models Guide Preclinical Development. PLoS ONE. 6(11). e27518–e27518. 40 indexed citations

17.

Westen, Gerard J. P. van, Jörg K. Wegner, Andreas Bender, Adriaan P. IJzerman, & Herman van Vlijmen. (2010). Mining protein dynamics from sets of crystal structures using “consensus structures”. Protein Science. 19(4). 742–752. 14 indexed citations

18.

Agrafiotis, Dimitris K., Deepak Bandyopadhyay, Jörg K. Wegner, & Herman van Vlijmen. (2007). Recent Advances in Chemoinformatics. Journal of Chemical Information and Modeling. 47(4). 1279–1293. 44 indexed citations

19.

Wegner, Jörg K., et al.. (2003). The compressed feature matrix?a fast method for feature based substructure search. Journal of Molecular Modeling. 9(4). 235–241. 32 indexed citations

20.

Wegner, Jörg K., et al.. (1973). Automatic determination of decay rates of single- and double-labelled samples with the aid of a programmable desk computer in off-line regime. Kerntechnik. 15(10). 467–472.

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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