David Schaller

861 citations
14 papers · 291 · h-index 7

Impact in

Papers in

    • Receptor Mechanisms and Signaling 4
    • Ion channel regulation and function 2
    • Protein Structure and Dynamics 2
    • Chemical Synthesis and Analysis 2
    • Genetics, Bioinformatics, and Biomedical Research 1
    • Computational Drug Discovery Methods 6

David Schaller

12 papers receiving 290 citations

Peers

David Schaller
Comparison fields: 5 of 82
  • Computational Theory and Mathematics 123
  • Organic Chemistry 91
  • Toxicology 9
  • Pharmacology 40
  • Molecular Biology 161
Replace Szymon Pach with:
Szymon Pach Germany
Lisa R. Thompson United Kingdom
Andy Vinter United Kingdom
George Agelis Greece
Tedman Ehlers United States
Bhanuranjan Das India
Arnaud LeTiran United States
Maicol Bissaro Italy
Noor Atatreh United Arab Emirates
Sabine Schultes Austria
David Schaller relative to Szymon Pach Germany Szymon Pach's profile →
Citations per field
00.5×1.5×2.4×
Szymon Pach · 1×
Citations per year

Countries citing papers authored by David Schaller

Since Specialization
Citations

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

Fields of papers citing papers by David Schaller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Schaller, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Schaller Line = papers co-authored together David Schaller links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2020167
2 201841
3 201920
4 201917
5 20209
6 20218
7 20228
8 20216
9 20176
10 20204
11 20253
12 20192
13 20240
14 20250

About David Schaller

David Schaller is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Radiology, Nuclear Medicine and Imaging and Materials Chemistry, having authored 14 papers that have together received 291 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Receptor Mechanisms and Signaling (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Ion channel regulation and function (2 papers), Enzyme Structure and Function (2 papers), Protein Structure and Dynamics (2 papers), Chemical Synthesis and Analysis (2 papers) and Genetics, Bioinformatics, and Biomedical Research (1 paper). The work is most often cited by research in Computational Theory and Mathematics (123 citations), Organic Chemistry (91 citations), Toxicology (9 citations), Pharmacology (40 citations) and Molecular Biology (161 citations). David Schaller has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Gerhard Wolber, Szymon Pach, David Machalz, Trung Ngoc Nguyen, Lihua Deng, Marcel Bermúdez, Miyase Gözde Gündüz, Gerald W. Zamponi, Holger Stark and Stefanie Hagenow. Their work appears in journals such as Molecular Informatics, ACS Medicinal Chemistry Letters, European Journal of Medicinal Chemistry, Wiley Interdisciplinary Reviews Computational Molecular Science and Journal of Medicinal Chemistry.

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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