Marcus Wieder

819 total citations
26 papers, 450 citations indexed

About

Marcus Wieder is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Marcus Wieder has authored 26 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 10 papers in Materials Chemistry. Recurrent topics in Marcus Wieder's work include Computational Drug Discovery Methods (14 papers), Protein Structure and Dynamics (11 papers) and Machine Learning in Materials Science (8 papers). Marcus Wieder is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Protein Structure and Dynamics (11 papers) and Machine Learning in Materials Science (8 papers). Marcus Wieder collaborates with scholars based in Austria, Italy and United States. Marcus Wieder's co-authors include Thierry Langer, Stefan Boresch, Thomas Seidel, Ugo Perricone, Anna Maria Almerico, John D. Chodera, Josh Fass, Gerhard F. Ecker, Oliver Wieder and Arthur Garon and has published in prestigious journals such as The Journal of Physical Chemistry B, Biochemical and Biophysical Research Communications and International Journal of Molecular Sciences.

In The Last Decade

Marcus Wieder

25 papers receiving 442 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcus Wieder Austria 13 287 188 122 53 46 26 450
Bryan VanSchouwen Canada 14 650 2.3× 158 0.8× 89 0.7× 32 0.6× 101 2.2× 33 799
Marta Amaral Germany 7 411 1.4× 205 1.1× 86 0.7× 28 0.5× 25 0.5× 8 629
Lydia Young United Kingdom 10 512 1.8× 75 0.4× 74 0.6× 51 1.0× 25 0.5× 13 812
Michael C. Owen Hungary 13 433 1.5× 70 0.4× 74 0.6× 38 0.7× 73 1.6× 35 707
Balázs Jójárt Hungary 12 311 1.1× 64 0.3× 64 0.5× 38 0.7× 55 1.2× 39 533
Guanglin Kuang Sweden 10 239 0.8× 176 0.9× 66 0.5× 20 0.4× 40 0.9× 21 444
Brian Michael United States 8 486 1.7× 121 0.6× 121 1.0× 37 0.7× 33 0.7× 9 803
Steven Ramsey United States 10 353 1.2× 219 1.2× 109 0.9× 8 0.2× 47 1.0× 14 465
Elke Reinartz Germany 7 574 2.0× 140 0.7× 98 0.8× 40 0.8× 48 1.0× 9 914
Saher A. Shaikh United States 13 446 1.6× 53 0.3× 37 0.3× 78 1.5× 113 2.5× 21 588

Countries citing papers authored by Marcus Wieder

Since Specialization
Citations

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

Fields of papers citing papers by Marcus Wieder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcus Wieder

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Wieder. A scholar is included among the top collaborators of Marcus Wieder 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 Wieder. Marcus Wieder 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.
Wang, Yuanqing, Michael S. Chen, Marcus Wieder, et al.. (2025). On the design space between molecular mechanics and machine learning force fields. Applied Physics Reviews. 12(2). 10 indexed citations
2.
Langer, Thierry, et al.. (2025). Architecture-Independent Absolute Solvation Free Energy Calculations with Neural Network Potentials. The Journal of Physical Chemistry Letters. 16(46). 12080–12086.
3.
Wieder, Marcus, et al.. (2025). Transferable Neural Network Potentials and Condensed Phase Properties. Journal of Chemical Information and Modeling. 65(18). 9483–9496. 2 indexed citations
4.
Woodcock, H. Lee, et al.. (2024). Reweighting from Molecular Mechanics Force Fields to the ANI-2x Neural Network Potential. Journal of Chemical Theory and Computation. 20(7). 2719–2728. 11 indexed citations
5.
Wieder, Marcus, et al.. (2023). Calculations of Absolute Solvation Free Energies with Transformato─Application to the FreeSolv Database Using the CGenFF Force Field. Journal of Chemical Theory and Computation. 19(17). 5988–5998. 11 indexed citations
6.
Wieder, Marcus, et al.. (2023). Protex—A Python utility for proton exchange in molecular dynamics simulations. Frontiers in Chemistry. 11. 1140896–1140896. 9 indexed citations
7.
8.
Wieder, Marcus, et al.. (2022). Improving Small Molecule pKa Prediction Using Transfer Learning With Graph Neural Networks. Frontiers in Chemistry. 10. 866585–866585. 23 indexed citations
9.
Schrempf, Anna, Dominik Kirchhofer, Gerald Timelthaler, et al.. (2022). POLθ processes ssDNA gaps and promotes replication fork progression in BRCA1-deficient cells. Cell Reports. 41(9). 111716–111716. 47 indexed citations
10.
Wieder, Marcus, et al.. (2022). Relative binding free energy calculations with transformato: A molecular dynamics engine-independent tool. Frontiers in Molecular Biosciences. 9. 954638–954638. 7 indexed citations
11.
Wieder, Marcus, Josh Fass, & John D. Chodera. (2021). Fitting quantum machine learning potentials to experimental free energy data: predicting tautomer ratios in solution. Chemical Science. 12(34). 11364–11381. 30 indexed citations
12.
Garon, Arthur, Marcus Wieder, Marien J. C. Houtman, et al.. (2019). Computational Identification of Novel Kir6 Channel Inhibitors. Frontiers in Pharmacology. 10. 549–549. 8 indexed citations
13.
Ilić, Marija, Predrag Kalaba, Johann Leban, et al.. (2018). A daily single dose of a novel modafinil analogue CE-123 improves memory acquisition and memory retrieval. Behavioural Brain Research. 343. 83–94. 19 indexed citations
14.
Perricone, Ugo, Marcus Wieder, Thomas Seidel, Thierry Langer, & Alessandro Padova. (2018). The Use of Dynamic Pharmacophore in Computer-Aided Hit Discovery: A Case Study. Methods in molecular biology. 1824. 317–333. 1 indexed citations
15.
Wieder, Marcus, Petra Scholze, Stefan Boresch, et al.. (2018). SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2– Benzodiazepine Site. Journal of Chemical Information and Modeling. 58(8). 1682–1696. 4 indexed citations
16.
Perricone, Ugo, Marcus Wieder, Thomas Seidel, et al.. (2017). A Molecular Dynamics–Shared Pharmacophore Approach to Boost Early‐Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator‐Activated Receptor α. ChemMedChem. 12(16). 1399–1407. 22 indexed citations
17.
Wieder, Marcus, Ugo Perricone, Thomas Seidel, Stefan Boresch, & Thierry Langer. (2016). Comparing pharmacophore models derived from crystal structures and from molecular dynamics simulations. Monatshefte für Chemie - Chemical Monthly. 147(3). 553–563. 15 indexed citations
18.
Wieder, Marcus, Ugo Perricone, Stefan Boresch, Thomas Seidel, & Thierry Langer. (2016). Evaluating the stability of pharmacophore features using molecular dynamics simulations. Biochemical and Biophysical Research Communications. 470(3). 685–689. 21 indexed citations
19.
Wieder, Marcus, Ugo Perricone, Thomas Seidel, & Thierry Langer. (2016). Pharmacophore Models Derived from Molecular Dynamics Simulations of Protein-Ligand Complexes: A Case Study. Natural Product Communications. 11(10). 1499–1504. 4 indexed citations
20.
Poli, Giulio, Marcus Wieder, Ke Song, et al.. (2015). Identification of the putative binding pocket of valerenic acid on GABAA receptors using docking studies and site‐directed mutagenesis. British Journal of Pharmacology. 172(22). 5403–5413. 25 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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