Konstantin Fackeldey
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Organic Chemistry
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Marcus WeberChristoph GorgullaHaribabu ArthanariGerhard WagnerPatrick D. FischerAndras BoeszoermenyiDavid A. ScottKrishna Mohan Das
- Topics
- Protein Structure and Dynamics (14 papers)Computational Drug Discovery Methods (10 papers)Machine Learning in Materials Science (4 papers)
- Journals
- NatureThe Journal of Chemical PhysicsSHILAP Revista de lepidopterología
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Konstantin Fackeldey
30 papers receiving 610 citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Molecular Biology 388
- Computational Theory and Mathematics 301
- Materials Chemistry 118
- Organic Chemistry 48
- Statistical and Nonlinear Physics 44
Countries citing papers authored by Konstantin Fackeldey
This map shows the geographic impact of Konstantin Fackeldey'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 Konstantin Fackeldey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konstantin Fackeldey more than expected).
Fields of papers citing papers by Konstantin Fackeldey
This network shows the impact of papers produced by Konstantin Fackeldey. 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 Konstantin Fackeldey. The network helps show where Konstantin Fackeldey may publish in the future.
Co-authorship network of co-authors of Konstantin Fackeldey
This figure shows the co-authorship network connecting the top 25 collaborators of Konstantin Fackeldey. A scholar is included among the top collaborators of Konstantin Fackeldey 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 Konstantin Fackeldey. Konstantin Fackeldey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 25 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | An open-source drug discovery platform enables ultra-large virtual screensbreakdown → | 395 |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | GenPCCA -- Markov State Models for Non-Equilibrium Steady States | 3 |
| 13 | 11 | |
| 14 | 5 | |
| 15 | 3 | |
| 16 | 4 | |
| 17 | 1 | |
| 18 | Soft Versus Hard Metastable Conformations in Molecular Simulations | 3 |
| 19 | 8 | |
| 20 | 11 |
About Konstantin Fackeldey
Konstantin Fackeldey is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Biophysics, having authored 33 papers that have together received 623 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (14 papers), Computational Drug Discovery Methods (10 papers) and Machine Learning in Materials Science (4 papers). The work is most often cited by research in Computational Theory and Mathematics (301 citations), Computational Mathematics (5 citations) and Drug Discovery (1 citation). Konstantin Fackeldey has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Marcus Weber, Christoph Gorgulla, Haribabu Arthanari, Gerhard Wagner, Patrick D. Fischer, Andras Boeszoermenyi, David A. Scott, Krishna Mohan Das, Zifu Wang and Dmytro S. Radchenko. Their work appears in journals such as Nature, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.
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.