Gerhard Heßler
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Health Informatics top 5%
Papers in
-
- Computational Drug Discovery Methods 29
-
- Chemical Synthesis and Analysis 12
- Protein Structure and Dynamics 8
- Receptor Mechanisms and Signaling 6
- Co-authors
- Thomas KlabundeKarl‐Heinz BaringhausHans MatterHorst KesslerMatthias HoffmannAndreas EversGerhard MüllerErich Graf von Roedern
- Journals
- Journal of Chemical Information and Modeling (9 papers)Journal of Medicinal Chemistry (7 papers)ChemMedChem (4 papers)Angewandte Chemie International Edition (3 papers)Journal of Cheminformatics (3 papers)
- Partner nations
- GermanyFranceUnited States
In The Last Decade
Gerhard Heßler
54 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 141
- Computational Theory and Mathematics 642
- Health Informatics 31
- Molecular Biology 1.5k
- Organic Chemistry 456
- Sensory Systems 69
Countries citing papers authored by Gerhard Heßler
This map shows the geographic impact of Gerhard Heßler'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 Gerhard Heßler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerhard Heßler more than expected).
Fields of papers citing papers by Gerhard Heßler
This network shows the impact of papers produced by Gerhard Heßler. 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 Gerhard Heßler. The network helps show where Gerhard Heßler may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gerhard Heßler, 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 | 2025 | 0 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 0 | |
| 5 | 2022 | 9 | |
| 6 | 2021 | 162 | |
| 7 | 2021 | 6 | |
| 8 | 2020 | 13 | |
| 9 | 2020 | 6 | |
| 10 | 2018 | 20 | |
| 11 | 2017 | 9 | |
| 12 | 2017 | 20 | |
| 13 | 2015 | 16 | |
| 14 | 2014 | 14 | |
| 15 | 2012 | 29 | |
| 16 | 2011 | 4 | |
| 17 | 2010 | 53 | |
| 18 | 2002 | 390 | |
| 19 | 2001 | 13 | |
| 20 | 1998 | 41 |
About Gerhard Heßler
Gerhard Heßler is a scholar working on Computational Theory and Mathematics, Molecular Biology, Environmental Chemistry, Organic Chemistry and Spectroscopy, having authored 56 papers that have together received 2.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (29 papers), Chemical Synthesis and Analysis (12 papers), Machine Learning in Materials Science (10 papers), Protein Structure and Dynamics (8 papers), Receptor Mechanisms and Signaling (6 papers), Microbial Natural Products and Biosynthesis (4 papers), Analytical Chemistry and Chromatography (4 papers) and Chemistry and Chemical Engineering (4 papers). The work is most often cited by research in Computational Theory and Mathematics (642 citations), Health Informatics (31 citations), Molecular Biology (1.5k citations), Organic Chemistry (456 citations) and Sensory Systems (69 citations). Gerhard Heßler has collaborated with scholars based in Germany, France and United States. Frequent co-authors include Thomas Klabunde, Karl‐Heinz Baringhaus, Hans Matter, Horst Kessler, Matthias Hoffmann, Andreas Evers, Gerhard Müller, Erich Graf von Roedern, Elisabeth Lohof and Christoph Grebner. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, ChemMedChem, Angewandte Chemie International Edition and Journal of Cheminformatics.
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.