Robbin Bouwmeester

1.2k total citations
27 papers, 593 citations indexed

About

Robbin Bouwmeester is a scholar working on Molecular Biology, Spectroscopy and Computational Theory and Mathematics. According to data from OpenAlex, Robbin Bouwmeester has authored 27 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 22 papers in Spectroscopy and 4 papers in Computational Theory and Mathematics. Recurrent topics in Robbin Bouwmeester's work include Advanced Proteomics Techniques and Applications (17 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Robbin Bouwmeester is often cited by papers focused on Advanced Proteomics Techniques and Applications (17 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Robbin Bouwmeester collaborates with scholars based in Belgium, United States and United Kingdom. Robbin Bouwmeester's co-authors include Lennart Martens, Sven Degroeve, Ralf Gabriels, Niels Hulstaert, Aurélie Hirschler, Christine Carapito, Tim Van Den Bossche, Peter Van den Broeck, Kyriakos Efthymiadis and Deirdre Cabooter and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Robbin Bouwmeester

26 papers receiving 586 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robbin Bouwmeester Belgium 12 475 376 88 72 38 27 593
Maria Reinecke Germany 6 318 0.7× 188 0.5× 21 0.2× 55 0.8× 43 1.1× 11 455
Wen‐Feng Zeng China 14 732 1.5× 513 1.4× 14 0.2× 30 0.4× 49 1.3× 23 879
Matthew The Germany 14 522 1.1× 382 1.0× 17 0.2× 33 0.5× 37 1.0× 27 652
Melanie Leveridge United Kingdom 9 271 0.6× 179 0.5× 30 0.3× 61 0.8× 18 0.5× 11 401
Hannes Planatscher Germany 13 263 0.6× 104 0.3× 38 0.4× 23 0.3× 36 0.9× 32 420
Ekaterina G. Deyanova United States 12 418 0.9× 378 1.0× 11 0.1× 32 0.4× 54 1.4× 15 592
Lev I. Levitsky Russia 14 585 1.2× 512 1.4× 8 0.1× 37 0.5× 27 0.7× 40 724
Ekaterina V. Ilgisonis Russia 11 360 0.8× 151 0.4× 13 0.1× 34 0.5× 19 0.5× 48 472
Reta Birhanu Kitata United States 11 331 0.7× 250 0.7× 8 0.1× 99 1.4× 19 0.5× 18 509
Frédéric Nikitin Switzerland 8 387 0.8× 215 0.6× 14 0.2× 13 0.2× 31 0.8× 13 488

Countries citing papers authored by Robbin Bouwmeester

Since Specialization
Citations

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

Fields of papers citing papers by Robbin Bouwmeester

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robbin Bouwmeester

This figure shows the co-authorship network connecting the top 25 collaborators of Robbin Bouwmeester. A scholar is included among the top collaborators of Robbin Bouwmeester 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 Robbin Bouwmeester. Robbin Bouwmeester 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.
Pérez‐Riverol, Yasset, Wout Bittremieux, William Stafford Noble, et al.. (2025). Open-Source and FAIR Research Software for Proteomics. Journal of Proteome Research. 24(5). 2222–2234. 6 indexed citations
2.
Gabriels, Ralf, et al.. (2025). Collisional Cross-Section Prediction for Multiconformational Peptide Ions with IM2Deep. Analytical Chemistry. 97(28). 15113–15121.
3.
Abrams, Grégory, Robbin Bouwmeester, Kévin Di Modica, et al.. (2025). Classification of Collagens via Peptide Ambiguation, in a Paleoproteomic LC-MS/MS-Based Taxonomic Pipeline. Journal of Proteome Research. 24(4). 1907–1925. 2 indexed citations
4.
Staes, An, Teresa Mendes Maia, Robbin Bouwmeester, et al.. (2024). Benefit of In Silico Predicted Spectral Libraries in Data-Independent Acquisition Data Analysis Workflows. Journal of Proteome Research. 23(6). 2078–2089. 8 indexed citations
5.
Bouwmeester, Robbin, Keith Richardson, Richard Denny, et al.. (2024). Predicting ion mobility collision cross sections and assessing prediction variation by combining conventional and data driven modeling. Talanta. 274. 125970–125970. 2 indexed citations
6.
Bouwmeester, Robbin, et al.. (2024). MS2Rescore 3.0 Is a Modular, Flexible, and User-Friendly Platform to Boost Peptide Identifications, as Showcased with MS Amanda 3.0. Journal of Proteome Research. 23(8). 3200–3207. 11 indexed citations
7.
Bouwmeester, Robbin, Luisa M. Welp, Aleksandar Chernev, et al.. (2024). Intensity and retention time prediction improves the rescoring of protein‐nucleic acid cross‐links. PROTEOMICS. 24(8). e2300144–e2300144. 2 indexed citations
8.
Koutrouli, Mikaela, Katerina Nastou, Robbin Bouwmeester, et al.. (2024). FAVA: high-quality functional association networks inferred from scRNA-seq and proteomics data. Bioinformatics. 40(2). 4 indexed citations
9.
Gabriels, Ralf, Robbin Bouwmeester, Siegfried Gessulat, et al.. (2023). ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics. Journal of Proteome Research. 22(2). 632–636. 14 indexed citations
10.
Bouwmeester, Robbin, Cristina Chiva, Eduard Sabidó, et al.. (2023). Updated MS²PIP web server supports cutting-edge proteomics applications. Nucleic Acids Research. 51(W1). W338–W342. 13 indexed citations
11.
Gabriels, Ralf, Robbin Bouwmeester, Tim Van Den Bossche, et al.. (2022). Sensitive and Specific Spectral Library Searching with CompOmics Spectral Library Searching Tool and Percolator. Journal of Proteome Research. 21(5). 1365–1370. 5 indexed citations
12.
Gabriels, Ralf, et al.. (2022). psm_utils: A High-Level Python API for Parsing and Handling Peptide-Spectrum Matches and Proteomics Search Results. Journal of Proteome Research. 22(2). 557–560. 3 indexed citations
13.
Bouwmeester, Robbin, Ralf Gabriels, Niels Hulstaert, Lennart Martens, & Sven Degroeve. (2021). DeepLC can predict retention times for peptides that carry as-yet unseen modifications. Nature Methods. 18(11). 1363–1369. 131 indexed citations
14.
Boone, Morgane, Pathmanaban Ramasamy, Jasper Zuallaert, et al.. (2021). Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit. Nature Communications. 12(1). 6414–6414. 5 indexed citations
15.
Kensert, Alexander, Robbin Bouwmeester, Kyriakos Efthymiadis, et al.. (2021). Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data. Analytical Chemistry. 93(47). 15633–15641. 34 indexed citations
16.
Bouwmeester, Robbin, Lennart Martens, & Sven Degroeve. (2020). Generalized Calibration Across Liquid Chromatography Setups for Generic Prediction of Small-Molecule Retention Times. Analytical Chemistry. 92(9). 6571–6578. 32 indexed citations
17.
Bouwmeester, Robbin, Ralf Gabriels, Tim Van Den Bossche, Lennart Martens, & Sven Degroeve. (2020). The Age of Data‐Driven Proteomics: How Machine Learning Enables Novel Workflows. PROTEOMICS. 20(21-22). e1900351–e1900351. 31 indexed citations
18.
Bouwmeester, Robbin, et al.. (2019). Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions. Bioinformatics. 35(24). 5243–5248. 40 indexed citations
19.
20.
Bouwmeester, Robbin, Lennart Martens, & Sven Degroeve. (2019). Comprehensive and Empirical Evaluation of Machine Learning Algorithms for Small Molecule LC Retention Time Prediction. Analytical Chemistry. 91(5). 3694–3703. 78 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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