Nikolaus Stiefl
- Computational Theory and Mathematics top 0.5%
- Molecular Biology top 10%
- Materials Chemistry top 10%
- Organic Chemistry top 10%
- Pharmacology top 10%
- Co-authors
- Gregory A. LandrumKnut BaumannPaolo ToscoNadine SchneiderAndrea ZalianiIan A. WatsonSereina RinikerFinton Sirockin
- Topics
- Computational Drug Discovery Methods (33 papers)Machine Learning in Materials Science (14 papers)Metabolomics and Mass Spectrometry Studies (5 papers)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Nikolaus Stiefl
42 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 144
- Computational Theory and Mathematics 779
- Molecular Biology 742
- Materials Chemistry 393
- Organic Chemistry 198
- Pharmacology 123
Countries citing papers authored by Nikolaus Stiefl
This map shows the geographic impact of Nikolaus Stiefl'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 Nikolaus Stiefl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nikolaus Stiefl more than expected).
Fields of papers citing papers by Nikolaus Stiefl
This network shows the impact of papers produced by Nikolaus Stiefl. 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 Nikolaus Stiefl. The network helps show where Nikolaus Stiefl may publish in the future.
Co-authorship network of co-authors of Nikolaus Stiefl
This figure shows the co-authorship network connecting the top 25 collaborators of Nikolaus Stiefl. A scholar is included among the top collaborators of Nikolaus Stiefl 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 Nikolaus Stiefl. Nikolaus Stiefl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 9 | |
| 4 | 13 | |
| 5 | 11 | |
| 6 | 5 | |
| 7 | 101 | |
| 8 | 103 | |
| 9 | 10 | |
| 10 | 1 | |
| 11 | 16 | |
| 12 | 1 | |
| 13 | 125 | |
| 14 | 97 | |
| 15 | 54 | |
| 16 | 1 | |
| 17 | 38 | |
| 18 | 110 | |
| 19 | 59 | |
| 20 | 39 |
About Nikolaus Stiefl
Nikolaus Stiefl is a scholar working on Computational Theory and Mathematics, Information Systems and Management and Molecular Biology, having authored 43 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (33 papers), Machine Learning in Materials Science (14 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). The work is most often cited by research in Computational Theory and Mathematics (779 citations), Molecular Biology (742 citations) and Materials Chemistry (393 citations). Nikolaus Stiefl has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Gregory A. Landrum, Knut Baumann, Paolo Tosco, Nadine Schneider, Andrea Zaliani, Ian A. Watson, Sereina Riniker, Finton Sirockin, Jean‐Louis Reymond and Mahendra Awale. Their work appears in journals such as Nature Communications, Journal of Molecular Biology and Nature Reviews Drug Discovery.
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.