David Diller

2.1k citations
70 papers · 1.7k · h-index 18

Impact in

Papers in

David Diller

67 papers receiving 1.6k citations

Peers

David Diller
Comparison fields: 5 of 147
  • Computational Theory and Mathematics 664
  • Molecular Biology 861
  • Pharmacology 85
  • Organic Chemistry 265
  • Pharmacology 117
Replace Andrea Zaliani with:
Andrea Zaliani Germany
Edward W. Lowe United States
Gregory R. Sliwoski United States
Nadine Schneider Germany
Scott P. Brown United States
Sudipto Mukherjee United States
Sandeepkumar Kothiwale United States
Mahendra Awale Switzerland
Jeremy J. Yang United States
Jeffrey J. Sutherland United States
David Diller relative to Andrea Zaliani Germany Andrea Zaliani's profile →
Citations per field
00.5×1.5×1.8×
Andrea Zaliani · 1×
Citations per year

Countries citing papers authored by David Diller

Since Specialization
Citations

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

Fields of papers citing papers by David Diller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Diller, 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 Diller Line = papers co-authored together David Diller links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001292
2 2008159
3 2003108
4 2003105
5 200685
6 200564
7 201061
8 199956
9 200255
10 200443
11 199941
12 200441
13 200139
14 200438
15 200237
16 202136
17 200536
18 199631
19 201718
20 199918

About David Diller

David Diller is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Spectroscopy and Radiology, Nuclear Medicine and Imaging, having authored 70 papers that have together received 1.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Protein Structure and Dynamics (10 papers), Chemical Synthesis and Analysis (9 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Analytical Chemistry and Chromatography (4 papers), Innovations in Medical Education (4 papers), Enzyme Structure and Function (4 papers) and Melanoma and MAPK Pathways (4 papers). The work is most often cited by research in Computational Theory and Mathematics (664 citations), Molecular Biology (861 citations), Pharmacology (85 citations), Organic Chemistry (265 citations) and Pharmacology (117 citations). David Diller has collaborated with scholars based in United States, Singapore and Kazakhstan. Frequent co-authors include Kenneth M. Merz, Jr., Anthony E. Klon, Christophe L. M. J. Verlinde, Doug W. Hobbs, Wim G. J. Hol, Douglas S. Auld, Robert Kirk DeLisle, Christopher P. Austin, Anton Simeonov and Ronald L. Johnson. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling, Proteins Structure Function and Bioinformatics, AEM Education and Training and Journal of Computer-Aided Molecular Design.

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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