Peter Schmidtke
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 8
- Molecular Biology top 5%
- Protein Structure and Dynamics 8
- Pharmacology top 2%
- Microbial Natural Products and Biosynthesis 3
- Microbiology top 5%
- Pharmacology top 5%
- Microbial Natural Products and Biosynthesis 3
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- Enzyme Structure and Function 4
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- Herbal Medicine Research Studies 2
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- Immune Cell Function and Interaction 2
- Immunotherapy and Immune Responses 2
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- Crystallography and molecular interactions 2
- Co-authors
- Pierre TufféryVincent Le GuillouxXavier BarrilF. Javier LuqueAxel Bidon‐ChanalFred ZeppJulien MaupetitSergio Ruiz‐Carmona
In The Last Decade
Peter Schmidtke
26 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Computational Theory and Mathematics 1.1k
- Molecular Biology 2.3k
- Pharmacology 355
- Microbiology 88
- Pharmacology 113
Countries citing papers authored by Peter Schmidtke
This map shows the geographic impact of Peter Schmidtke'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 Peter Schmidtke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Schmidtke more than expected).
Fields of papers citing papers by Peter Schmidtke
This network shows the impact of papers produced by Peter Schmidtke. 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 Peter Schmidtke. The network helps show where Peter Schmidtke may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Schmidtke, 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 | 2021 | 8 | |
| 2 | 2020 | 6 | |
| 3 | 2017 | 11 | |
| 4 | 2016 | 70 | |
| 5 | rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acidsbreakdown → | 2014 | 409 |
| 6 | 2013 | 31 | |
| 7 | 2011 | 166 | |
| 8 | 2010 | 215 | |
| 9 | 2010 | 227 | |
| 10 | 2010 | 60 | |
| 11 | 2009 | 20 | |
| 12 | Fpocket: An open source platform for ligand pocket detectionbreakdown → | 2009 | 1048 |
| 13 | 2008 | 96 | |
| 14 | 2005 | 70 | |
| 15 | 2005 | 39 | |
| 16 | 2005 | 8 | |
| 17 | 2005 | 29 | |
| 18 | 2005 | 107 | |
| 19 | 2003 | 5 | |
| 20 | 2002 | 101 |
About Peter Schmidtke
Peter Schmidtke is a scholar working on Computational Theory and Mathematics, Pharmacology and Complementary and alternative medicine, having authored 26 papers that have together received 3.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Computational Drug Discovery Methods (8 papers), Enzyme Structure and Function (4 papers), Microbial Natural Products and Biosynthesis (3 papers), Herbal Medicine Research Studies (2 papers), Immune Cell Function and Interaction (2 papers), Crystallography and molecular interactions (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Molecular Biology (2.3k citations) and Pharmacology (355 citations). Peter Schmidtke has collaborated with scholars based in Spain, Germany and France. Frequent co-authors include Pierre Tufféry, Vincent Le Guilloux, Xavier Barril, F. Javier Luque, Axel Bidon‐Chanal, Fred Zepp, Julien Maupetit, Sergio Ruiz‐Carmona, Claudius U. Meyer and Nicolas K. Shinada. Their work appears in journals such as International Journal of Molecular Sciences, Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling, Nature Chemistry and Pediatric Rheumatology.
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.