Martin Ståhl

13.8k citations
119 papers · 10.4k indexed · 4 hit papers · h-index 45
Topics
Computational Drug Discovery Methods (32 papers)Protein Structure and Dynamics (16 papers)Chemical Synthesis and Analysis (16 papers)
Partner nations
SwitzerlandGermanyCanada

In The Last Decade

Martin Ståhl

115 papers receiving 10.1k citations

Hit Papers

Inhibition of SARS-CoV...2004202620112018202020042010201050010001.5k

Peers

Martin Ståhl
Comparison fields: 5 of 182
  • Molecular Biology 4.6k
  • Organic Chemistry 2.8k
  • Computational Theory and Mathematics 2.4k
  • Infectious Diseases 1.8k
  • Pharmaceutical Science 943
Replace Bernd Kuhn with:
Bernd Kuhn Switzerland
Ernesto Freire United States
Garland R. Marshall United States
Adrian J. Mulholland United Kingdom
Holger Gohlke Germany
Per Artursson Sweden
John C. Vederas Canada
William Trager United States
Dietmar Schomburg Germany
Martin Ståhl relative to Bernd Kuhn Switzerland Bernd Kuhn's profile →
Citations per field
00.5×2.5×
Bernd Kuhn · 1×
Citations per year

Countries citing papers authored by Martin Ståhl

Since Specialization
Citations

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

Fields of papers citing papers by Martin Ståhl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Ståhl

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Ståhl. A scholar is included among the top collaborators of Martin Ståhl 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 Martin Ståhl. Martin Ståhl 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
#WorkIndexed citations
1 4
2 1
3 3
4 4
5 19
6 27
7 91
8 11
9 26
10 35
11 59
12 37
13 83
14 42
15 163
16 64
17 140
18 36
19 46
20 44

About Martin Ståhl

Martin Ståhl is a scholar working on Computational Theory and Mathematics, Endocrinology and Organic Chemistry, having authored 119 papers that have together received 10.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (32 papers), Protein Structure and Dynamics (16 papers) and Chemical Synthesis and Analysis (16 papers). The work is most often cited by research in Pharmaceutical Science (943 citations), Computational Theory and Mathematics (2.4k citations) and Organic Chemistry (2.8k citations). Martin Ståhl has collaborated with scholars based in Switzerland, Germany and Canada. Frequent co-authors include Bernd Kuhn, Caterina Bissantz, Tanja Schulz‐Gasch, Hans‐Joachim Böhm, Matthias Rarey, Manfred Kansy, David W. Banner, U. Obst-Sander, Klaus Müller and Stefanie Bendels. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

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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