David W. Will
- Molecular Biology top 10%
- Advanced biosensing and bioanalysis techniques 13
- DNA and Nucleic Acid Chemistry 13
- RNA Interference and Gene Delivery 6
- Protein Structure and Dynamics 4
- Chemical Synthesis and Analysis 4
- Organic Chemistry top 5%
- Click Chemistry and Applications 4
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- Computational Drug Discovery Methods 5
- Inorganic Chemistry top 10%
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- Blood Coagulation and Thrombosis Mechanisms 8
- Co-authors
- Eugen UhlmannGerhard BreipohlAnusch PeymanMarc NazaréVolkmar WehnerHans MatterHerman SchreuderMatthias Urmann
- Journals
- Bioorganic & Medicinal Chemistry Letters (4 papers)Angewandte Chemie International Edition (4 papers)Journal of Medicinal Chemistry (3 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
David W. Will
36 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 88
- Physical and Theoretical Chemistry 207
- Molecular Biology 1.1k
- Organic Chemistry 407
- Computational Theory and Mathematics 142
- Inorganic Chemistry 120
Countries citing papers authored by David W. Will
This map shows the geographic impact of David W. Will'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 W. Will with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David W. Will more than expected).
Fields of papers citing papers by David W. Will
This network shows the impact of papers produced by David W. Will. 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 W. Will. The network helps show where David W. Will may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David W. Will, 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 | 2022 | 5 | |
| 2 | 2021 | 21 | |
| 3 | 2016 | 28 | |
| 4 | 2014 | 14 | |
| 5 | 2011 | 41 | |
| 6 | 2009 | 238 | |
| 7 | 2004 | 13 | |
| 8 | 2004 | 17 | |
| 9 | 2004 | 11 | |
| 10 | 2004 | 14 | |
| 11 | 2004 | 110 | |
| 12 | 2001 | 10 | |
| 13 | 1998 | 365 | |
| 14 | 1997 | 4 | |
| 15 | 1996 | 69 | |
| 16 | 1993 | 5 | |
| 17 | 1992 | 113 | |
| 18 | 1992 | 6 | |
| 19 | 1992 | 35 | |
| 20 | 1988 | 1 |
About David W. Will
David W. Will is a scholar working on Hematology, Molecular Biology, Organic Chemistry, Computational Theory and Mathematics and Nutrition and Dietetics, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (13 papers), DNA and Nucleic Acid Chemistry (13 papers), Blood Coagulation and Thrombosis Mechanisms (8 papers), RNA Interference and Gene Delivery (6 papers), Computational Drug Discovery Methods (5 papers), Click Chemistry and Applications (4 papers), Protein Structure and Dynamics (4 papers) and Chemical Synthesis and Analysis (4 papers). The work is most often cited by research in Physical and Theoretical Chemistry (207 citations), Molecular Biology (1.1k citations), Organic Chemistry (407 citations), Computational Theory and Mathematics (142 citations) and Inorganic Chemistry (120 citations). David W. Will has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Eugen Uhlmann, Gerhard Breipohl, Anusch Peyman, Marc Nazaré, Volkmar Wehner, Hans Matter, Herman Schreuder, Matthias Urmann, Armin Bauer and Kurt Ritter. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Angewandte Chemie International Edition, Journal of Medicinal Chemistry, Nucleic Acids Research and Tetrahedron.
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.