Tim Hempel

1.0k total citations
10 papers, 187 citations indexed

About

Tim Hempel is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Tim Hempel has authored 10 papers receiving a total of 187 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 3 papers in Infectious Diseases. Recurrent topics in Tim Hempel's work include Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Tim Hempel is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Tim Hempel collaborates with scholars based in Germany, United States and Sweden. Tim Hempel's co-authors include Frank Noé, Simon Olsson, Markus Hoffmann, Lluı́s Raich, Stefan Pöhlmann, Nurit P. Azouz, Marc E. Rothenberg, Andrea M. Klingler, Christoph Wehmeyer and Martin K. Scherer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Chemical Science.

In The Last Decade

Tim Hempel

9 papers receiving 186 citations

Peers

Tim Hempel

MB

ID

CTM

MC

AMPO

Nevena Ilieva Bulgaria

Chris Chipot France

Nguyen Quoc Thai Vietnam

Jonathan Borowsky United States

Chen Bai China

Upasana L. Mallimadugula United States

Artur Meller United States

Andrea Saltalamacchia Italy

Jack A. Henderson United States

Nevena Ilieva Bulgaria

Tim Hempel

126 ×1.2

MB

19 ×0.3

ID

36 ×0.6

CTM

23 ×0.7

MC

11 ×0.7

AMPO

Citations per year, relative to Tim Hempel Tim Hempel (= 1×) peers Nevena Ilieva

Countries citing papers authored by Tim Hempel

Since Specialization

Citations

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

Fields of papers citing papers by Tim Hempel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Hempel

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

All Works

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10 of 10 papers shown

1.

Hempel, Tim, Jonathan H. Shrimp, Nina Moor, et al.. (2025). Simulations and active learning enable efficient identification of an experimentally-validated broad coronavirus inhibitor. Nature Communications. 16(1). 6949–6949.

2.

Narayanan, Chitra, Tim Hempel, Khushboo Bafna, et al.. (2023). Conformational exchange divergence along the evolutionary pathway of eosinophil-associated ribonucleases. Structure. 31(3). 329–342.e4. 5 indexed citations

3.

Mardt, Andreas, Tim Hempel, Cecilia Clementi, & Frank Noé. (2022). Deep learning to decompose macromolecules into independent Markovian domains. Nature Communications. 13(1). 15 indexed citations

4.

Hempel, Tim, Simon Olsson, & Frank Noé. (2022). Markov field models: Scaling molecular kinetics approaches to large molecular machines. Current Opinion in Structural Biology. 77. 102458–102458. 9 indexed citations

5.

Hempel, Tim, et al.. (2021). Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes. Proceedings of the National Academy of Sciences. 118(31). 14 indexed citations

6.

Hempel, Tim, Nadine Krüger, Lluı́s Raich, et al.. (2021). Synergistic inhibition of SARS-CoV-2 cell entry by otamixaban and covalent protease inhibitors: pre-clinical assessment of pharmacological and molecular properties. Chemical Science. 12(38). 12600–12609. 15 indexed citations

7.

Hempel, Tim, Nuria Plattner, & Frank Noé. (2020). Coupling of Conformational Switches in Calcium Sensor Unraveled with Local Markov Models and Transfer Entropy. Journal of Chemical Theory and Computation. 16(4). 2584–2593. 10 indexed citations

8.

Hempel, Tim, Lluı́s Raich, Simon Olsson, et al.. (2020). Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat. Chemical Science. 12(3). 983–992. 76 indexed citations

9.

Wehmeyer, Christoph, Martin K. Scherer, Tim Hempel, et al.. (2018). Introduction to Markov state modeling with the PyEMMA software [Article v1.0]. 1(1). 5965–5965. 40 indexed citations

10.

Wehmeyer, Christoph, Martin K. Scherer, Tim Hempel, et al.. (2018). Introduction to Markov state modeling with the PyEMMA software — v1.0. 3 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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