Marcus Weber

4.2k total citations · 1 hit paper
119 papers, 3.2k citations indexed

About

Marcus Weber is a scholar working on Molecular Biology, Computational Theory and Mathematics and Spectroscopy. According to data from OpenAlex, Marcus Weber has authored 119 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 23 papers in Computational Theory and Mathematics and 20 papers in Spectroscopy. Recurrent topics in Marcus Weber's work include Protein Structure and Dynamics (39 papers), Computational Drug Discovery Methods (22 papers) and Markov Chains and Monte Carlo Methods (13 papers). Marcus Weber is often cited by papers focused on Protein Structure and Dynamics (39 papers), Computational Drug Discovery Methods (22 papers) and Markov Chains and Monte Carlo Methods (13 papers). Marcus Weber collaborates with scholars based in Germany, United States and Austria. Marcus Weber's co-authors include Peter Deuflhard, Rainer Haag, Susanna Röblitz, Oliver Seitz, Jens Dernedde, Christoph A. Schalley, Beate Koksch, Stefan Hecht, Christina Gräf and Ernst‐Walter Knapp and has published in prestigious journals such as Science, Angewandte Chemie International Edition and The Journal of Chemical Physics.

In The Last Decade

Marcus Weber

108 papers receiving 3.0k citations

Hit Papers

Multivalency as a Chemical Organization and Action Principle 2012 2026 2016 2021 2012 250 500 750
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.

  1. Multivalency as a Chemical Organization and Action Principle
    2012 846 citations Marcus Weber et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcus Weber Germany 23 1.9k 564 419 355 272 119 3.2k
Michel A. Cuendet Switzerland 22 2.1k 1.1× 577 1.0× 490 1.2× 268 0.8× 383 1.4× 54 4.0k
Francesco Rao Germany 26 2.2k 1.1× 370 0.7× 458 1.1× 223 0.6× 393 1.4× 48 2.8k
Yuhong Zhang China 11 2.7k 1.4× 418 0.7× 630 1.5× 275 0.8× 615 2.3× 39 4.1k
Xiaolin Cheng United States 42 2.7k 1.4× 470 0.8× 516 1.2× 273 0.8× 611 2.2× 175 5.1k
James L. Thomas United States 44 1.6k 0.9× 302 0.5× 479 1.1× 220 0.6× 112 0.4× 290 7.6k
Jérôme Hénin France 25 2.7k 1.4× 232 0.4× 662 1.6× 299 0.8× 746 2.7× 53 3.8k
François Dehez France 29 1.6k 0.9× 970 1.7× 745 1.8× 628 1.8× 450 1.7× 86 3.4k
Donald Hamelberg United States 32 3.8k 2.0× 483 0.9× 905 2.2× 561 1.6× 731 2.7× 107 4.6k
Fabrizio Marinelli United States 20 1.9k 1.0× 204 0.4× 647 1.5× 367 1.0× 483 1.8× 35 2.8k

Countries citing papers authored by Marcus Weber

Since Specialization
Citations

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

Fields of papers citing papers by Marcus Weber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcus Weber

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Weber. A scholar is included among the top collaborators of Marcus Weber 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 Marcus Weber. Marcus Weber 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.
Natarajan, Vijay, et al.. (2025). Topological Analysis Reveals Multiple Pathways in Molecular Dynamics. Journal of Chemical Theory and Computation. 21(20). 10385–10397.
2.
Weber, Marcus, et al.. (2024). Learning Koopman eigenfunctions of stochastic diffusions with optimal importance sampling and ISOKANN. Journal of Mathematical Physics. 65(1). 2 indexed citations
3.
Koprucki, Thomas, Christoph Lehrenfeld, Marco Reidelbach, et al.. (2023). Research-data management planning in the German mathematical community. GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen). 40–47. 1 indexed citations
4.
Fackeldey, Konstantin, et al.. (2023). Coarse-Grained MD Simulations of Opioid Interactions with the μ-Opioid Receptor and the Surrounding Lipid Membrane. SHILAP Revista de lepidopterología. 3(2). 263–275. 1 indexed citations
5.
Fackeldey, Konstantin, et al.. (2023). Augmented ant colony algorithm for virtual drug discovery. Journal of Mathematical Chemistry. 62(2). 367–385.
6.
Weber, Marcus, et al.. (2022). Parameter estimation on multivalent ITC data sets. Scientific Reports. 12(1). 13402–13402. 1 indexed citations
7.
Weber, Marcus, et al.. (2022). A review of Girsanov reweighting and of square root approximation for building molecular Markov state models. Journal of Mathematical Physics. 63(12). 13 indexed citations
8.
Weber, Marcus, et al.. (2022). Assessing transition rates as functions of environmental variables. The Journal of Chemical Physics. 157(22). 224103–224103. 2 indexed citations
9.
Weber, Marcus, et al.. (2021). The Augmented Jump Chain. Advanced Theory and Simulations. 4(4). 2 indexed citations
10.
Emmerling, Franziska, et al.. (2020). Effect of Choice of Solvent on Crystallization Pathway of Paracetamol: An Experimental and Theoretical Case Study. Crystals. 10(12). 1107–1107. 11 indexed citations
11.
Weber, Marcus, et al.. (2020). ISOKANN: Invariant subspaces of Koopman operators learned by a neural network. The Journal of Chemical Physics. 153(11). 114109–114109. 12 indexed citations
12.
Vecchio, Giovanna Del, Dominika Łabuz, Julia Temp, et al.. (2020). Author Correction: pKa of opioid ligands as a discriminating factor for side effects. Scientific Reports. 10(1). 4366–4366. 1 indexed citations
13.
Oehlmann, Jörg, Carsten Prasse, Ulrike Schulte‐Oehlmann, et al.. (2019). What you extract is what you see: Optimising the preparation of water and wastewater samples for in vitro bioassays. Water Research. 152. 47–60. 57 indexed citations
14.
Vecchio, Giovanna Del, Dominika Łabuz, Julia Temp, et al.. (2019). pKa of opioid ligands as a discriminating factor for side effects. Scientific Reports. 9(1). 19344–19344. 23 indexed citations
15.
Spahn, Viola, Giovanna Del Vecchio, Antonio Rodríguez‐Gaztelumendi, et al.. (2018). Opioid receptor signaling, analgesic and side effects induced by a computationally designed pH-dependent agonist. Scientific Reports. 8(1). 8965–8965. 49 indexed citations
16.
Heida, Martin, et al.. (2018). Estimation of the infinitesimal generator by square-root approximation. Journal of Physics Condensed Matter. 30(42). 425201–425201. 19 indexed citations
17.
Fackeldey, Konstantin, Amir Niknejad, & Marcus Weber. (2017). Finding metastabilities in reversible Markov chains based on incomplete sampling. Special Matrices. 5(1). 73–81.
18.
Spahn, Viola, Giovanna Del Vecchio, Dominika Łabuz, et al.. (2017). A nontoxic pain killer designed by modeling of pathological receptor conformations. Science. 355(6328). 966–969. 174 indexed citations
19.
Metzner, Philipp, Marcus Weber, & Christof Schütte. (2010). Observation uncertainty in reversible Markov chains. Physical Review E. 82(3). 31114–31114. 9 indexed citations
20.
Guerler, Aysam, et al.. (2007). Selection and flexible optimization of binding modes from conformation ensembles. Biosystems. 92(1). 42–48. 6 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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