Eric-Wubbo Lameijer

21.3k total citations
8 papers, 265 citations indexed

About

Eric-Wubbo Lameijer is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Eric-Wubbo Lameijer has authored 8 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 1 paper in Pharmacology. Recurrent topics in Eric-Wubbo Lameijer's work include Computational Drug Discovery Methods (5 papers), Chemical Synthesis and Analysis (2 papers) and Receptor Mechanisms and Signaling (2 papers). Eric-Wubbo Lameijer is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Chemical Synthesis and Analysis (2 papers) and Receptor Mechanisms and Signaling (2 papers). Eric-Wubbo Lameijer collaborates with scholars based in Netherlands, United Kingdom and China. Eric-Wubbo Lameijer's co-authors include Adriaan P. IJzerman, Thomas Bäck, Joost N. Kok, Kai Ye, Margot W. Beukers, P. Eline Slagboom, Yanju Zhang, Mingchao Xie, Kuan‐lin Huang and Jie Ning and has published in prestigious journals such as Nature Medicine, Bioinformatics and Journal of Medicinal Chemistry.

In The Last Decade

Eric-Wubbo Lameijer

7 papers receiving 254 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric-Wubbo Lameijer Netherlands 7 179 124 36 31 29 8 265
Christos Kannas Cyprus 7 161 0.9× 110 0.9× 37 1.0× 33 1.1× 13 0.4× 18 246
Timothy Sheils United States 9 222 1.2× 130 1.0× 19 0.5× 16 0.5× 12 0.4× 12 313
Finton Sirockin Switzerland 12 251 1.4× 122 1.0× 65 1.8× 8 0.3× 80 2.8× 23 386
Juan Martinez‐Sanz France 6 244 1.4× 109 0.9× 49 1.4× 14 0.5× 13 0.4× 9 329
Rajendra Kristam India 9 122 0.7× 120 1.0× 23 0.6× 5 0.2× 41 1.4× 11 239
Yann Gaston‐Mathé France 7 160 0.9× 147 1.2× 73 2.0× 29 0.9× 13 0.4× 13 259
Ryan T. Koehler United States 9 150 0.8× 87 0.7× 13 0.4× 11 0.4× 28 1.0× 11 196
Niclas Tue Hansen Denmark 6 252 1.4× 80 0.6× 29 0.8× 34 1.1× 23 0.8× 7 389
Eli Fernández‐de Gortari Mexico 10 174 1.0× 132 1.1× 29 0.8× 12 0.4× 31 1.1× 18 278
Dominique Sydow Germany 9 243 1.4× 177 1.4× 46 1.3× 12 0.4× 43 1.5× 15 356

Countries citing papers authored by Eric-Wubbo Lameijer

Since Specialization
Citations

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

Fields of papers citing papers by Eric-Wubbo Lameijer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric-Wubbo Lameijer. 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 Eric-Wubbo Lameijer. The network helps show where Eric-Wubbo Lameijer may publish in the future.

Co-authorship network of co-authors of Eric-Wubbo Lameijer

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

All Works

8 of 8 papers shown
1.
Ye, Kai, Jiayin Wang, Reyka G. Jayasinghe, et al.. (2015). Systematic discovery of complex insertions and deletions in human cancers. Nature Medicine. 22(1). 97–104. 66 indexed citations
2.
Zhang, Yanju, Eric-Wubbo Lameijer, Peter A.C. ’t Hoen, et al.. (2012). PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data. Bioinformatics. 28(4). 479–486. 19 indexed citations
3.
Lameijer, Eric-Wubbo, et al.. (2007). Designing Active Template Molecules by Combining Computational De Novo Design and Human Chemist's Expertise. Journal of Medicinal Chemistry. 50(8). 1925–1932. 11 indexed citations
4.
Lameijer, Eric-Wubbo, Joost N. Kok, Thomas Bäck, & Adriaan P. IJzerman. (2006). Mining a Chemical Database for Fragment Co-occurrence:  Discovery of “Chemical Clichés”. Journal of Chemical Information and Modeling. 46(2). 553–562. 35 indexed citations
5.
Ye, Kai, Eric-Wubbo Lameijer, Margot W. Beukers, & Adriaan P. IJzerman. (2006). A two‐entropies analysis to identify functional positions in the transmembrane region of class A G protein‐coupled receptors. Proteins Structure Function and Bioinformatics. 63(4). 1018–1030. 33 indexed citations
6.
Lameijer, Eric-Wubbo, Joost N. Kok, Thomas Bäck, & Adriaan P. IJzerman. (2006). The Molecule Evoluator. An Interactive Evolutionary Algorithm for the Design of Drug-Like Molecules. Journal of Chemical Information and Modeling. 46(2). 545–552. 72 indexed citations
7.
Lameijer, Eric-Wubbo, Adriaan P. IJzerman, & Joost N. Kok. (2005). The molecule evoluator. 1969–1976.
8.
Lameijer, Eric-Wubbo, Thomas Bäck, Joost N. Kok, & Adriaan P. IJzerman. (2005). Evolutionary Algorithms in Drug Design. Natural Computing. 4(3). 177–243. 29 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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