Markus Sitzmann
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 10%
- Pharmacogenetics and Drug Metabolism
Papers in
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- Computational Drug Discovery Methods 8
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- Metabolomics and Mass Spectrometry Studies 3
- Chemical Synthesis and Analysis 3
- Protein Structure and Dynamics 2
- Co-authors
- Marc C. Nicklaus (8 shared papers)Megan L. Peach (4 shared papers)Alexey Zakharov (3 shared papers)Chenzhong Liao (2 shared papers)Angelo Pugliese (2 shared papers)Igor Filippov (3 shared papers)Wolf‐Dietrich Ihlenfeldt (2 shared papers)Christopher Southan (2 shared papers)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Future Medicinal Chemistry (2 papers)SAR and QSAR in environmental research (1 paper)Perspectives in Drug Discovery and Design (1 paper)Journal of Computer-Aided Molecular Design (1 paper)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
Markus Sitzmann
12 papers receiving 505 citations
Peers
Comparison fields: 5 of 90
- Computational Theory and Mathematics 334
- Pharmacology 53
- Molecular Biology 292
- Spectroscopy 65
- Organic Chemistry 98
Countries citing papers authored by Markus Sitzmann
This map shows the geographic impact of Markus Sitzmann'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 Markus Sitzmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Sitzmann more than expected).
Fields of papers citing papers by Markus Sitzmann
This network shows the impact of papers produced by Markus Sitzmann. 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 Markus Sitzmann. The network helps show where Markus Sitzmann may publish in the future.
Co-authors
The 17 scholars most cited alongside Markus Sitzmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 117 | |
| 2 | 2014 | 97 | |
| 3 | 2010 | 52 | |
| 4 | 2012 | 51 | |
| 5 | 2014 | 43 | |
| 6 | 2008 | 41 | |
| 7 | 2014 | 31 | |
| 8 | 2013 | 29 | |
| 9 | 2012 | 29 | |
| 10 | 2000 | 22 | |
| 11 | 2012 | 17 | |
| 12 | 2004 | 1 |
About Markus Sitzmann
Markus Sitzmann is a scholar working on Computational Theory and Mathematics, Molecular Biology, Spectroscopy, Pharmacology and Materials Chemistry, having authored 12 papers that have together received 530 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Analytical Chemistry and Chromatography (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Chemical Synthesis and Analysis (3 papers), Protein Structure and Dynamics (2 papers), Molecular spectroscopy and chirality (1 paper) and Nonlinear Optical Materials Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (334 citations), Pharmacology (53 citations), Molecular Biology (292 citations), Spectroscopy (65 citations) and Organic Chemistry (98 citations). Markus Sitzmann has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Marc C. Nicklaus, Megan L. Peach, Alexey Zakharov, Chenzhong Liao, Angelo Pugliese, Igor Filippov, Wolf‐Dietrich Ihlenfeldt, Christopher Southan, Sorel Mureşan and Laura Guasch. Their work appears in journals such as Journal of Chemical Information and Modeling, Future Medicinal Chemistry, SAR and QSAR in environmental research, Perspectives in Drug Discovery and Design and Journal of Computer-Aided Molecular Design.
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.