David W. Sheppard

795 total citations
19 papers, 558 citations indexed

About

David W. Sheppard is a scholar working on Molecular Biology, Materials Chemistry and Organic Chemistry. According to data from OpenAlex, David W. Sheppard has authored 19 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Materials Chemistry and 5 papers in Organic Chemistry. Recurrent topics in David W. Sheppard's work include Computational Drug Discovery Methods (5 papers), Enzyme Structure and Function (4 papers) and Atmospheric chemistry and aerosols (3 papers). David W. Sheppard is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Enzyme Structure and Function (4 papers) and Atmospheric chemistry and aerosols (3 papers). David W. Sheppard collaborates with scholars based in United Kingdom, United States and Israel. David W. Sheppard's co-authors include J. A. Kerr, Neil A. Burton, Ian H. Hillier, Pieter F. W. Stouten, Martin J. Slater, R. D. Hill, R. A. Cox, R. A. Cox, Monica M. Olcina and Christopher Wells and has published in prestigious journals such as Journal of the American Chemical Society, Environmental Science & Technology and Chemical Communications.

In The Last Decade

David W. Sheppard

19 papers receiving 539 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David W. Sheppard United Kingdom 13 313 115 103 87 82 19 558
Kevin R. Condroski United States 12 197 0.6× 15 0.1× 25 0.2× 63 0.7× 303 3.7× 18 575
Chia‐Ning Yang Taiwan 16 304 1.0× 23 0.2× 44 0.4× 77 0.9× 278 3.4× 54 857
Russell A. Judge United States 20 642 2.1× 76 0.7× 68 0.7× 667 7.7× 77 0.9× 39 1.2k
F. C. Wireko United States 12 110 0.4× 20 0.2× 37 0.4× 156 1.8× 182 2.2× 35 579
Cheng‐Chi Chuang United States 13 202 0.6× 56 0.5× 37 0.4× 18 0.2× 39 0.5× 21 507
John Eksterowicz United States 16 374 1.2× 9 0.1× 198 1.9× 73 0.8× 272 3.3× 26 886
L.J. DeLucas United States 14 344 1.1× 19 0.2× 12 0.1× 162 1.9× 40 0.5× 30 551
Sanjay R. Chemburkar United States 13 176 0.6× 17 0.1× 46 0.4× 384 4.4× 300 3.7× 17 845
Katty Wan United States 11 541 1.7× 9 0.1× 17 0.2× 36 0.4× 46 0.6× 15 887
Mohammad Hossein Karimi‐Jafari Iran 12 258 0.8× 9 0.1× 75 0.7× 42 0.5× 46 0.6× 36 416

Countries citing papers authored by David W. Sheppard

Since Specialization
Citations

This map shows the geographic impact of David W. Sheppard'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. Sheppard 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. Sheppard more than expected).

Fields of papers citing papers by David W. Sheppard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David W. Sheppard

This figure shows the co-authorship network connecting the top 25 collaborators of David W. Sheppard. A scholar is included among the top collaborators of David W. Sheppard based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David W. Sheppard. David W. Sheppard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Klingler, Franca‐Maria, et al.. (2020). A small-molecule ARTS mimetic promotes apoptosis through degradation of both XIAP and Bcl-2. Cell Death and Disease. 11(6). 483–483. 22 indexed citations
2.
Brown, Nathan, Peter J. Cox, Mark Davies, et al.. (2018). Big Data in Drug Discovery. Progress in medicinal chemistry. 57(1). 277–356. 39 indexed citations
3.
Richardson, Christine M., et al.. (2015). Classifying shape coverage in fragment libraries using a fingerprinting approach. Bioorganic & Medicinal Chemistry Letters. 25(10). 2089–2095. 5 indexed citations
4.
Sheppard, David W., Michael E. Lipkin, Carolyn Harris, Cornel Catana, & Pieter F. W. Stouten. (2014). Strategies for Small Molecule Library Design. Current Pharmaceutical Design. 20(20). 3314–3322. 12 indexed citations
5.
Hewings, David S., O. Fedorov, P. Filippakopoulos, et al.. (2013). Optimization of 3,5-Dimethylisoxazole Derivatives as Potent Bromodomain Ligands. Journal of Medicinal Chemistry. 56(8). 3217–3227. 103 indexed citations
6.
Sheppard, David W., et al.. (2013). Building in molecular diversity for targeted libraries. Drug Discovery Today Technologies. 10(4). e461–e466. 3 indexed citations
7.
Hill, R. D., et al.. (2011). The Design and Application of Target-Focused Compound Libraries. Combinatorial Chemistry & High Throughput Screening. 14(6). 521–531. 82 indexed citations
8.
Pollack, Scott J., Kim S. Beyer, Christopher Lock, et al.. (2011). A comparative study of fragment screening methods on the p38α kinase: new methods, new insights. Journal of Computer-Aided Molecular Design. 25(7). 677–687. 26 indexed citations
9.
Ahrens, Thomas, Andreas Bergner, David W. Sheppard, & Doris Hafenbradl. (2011). Efficient Hit-Finding Approaches for Histone Methyltransferases: The Key Parameters. SLAS DISCOVERY. 17(1). 85–98. 2 indexed citations
10.
Sharma, R.P., et al.. (2010). Inhibitors of PIM-1 Kinase: A Computational Analysis of the Binding Free Energies of a Range of Imidazo [1,2-b] Pyridazines. Journal of Chemical Information and Modeling. 50(3). 368–379. 16 indexed citations
11.
Sheppard, David W., Neil A. Burton, & Ian H. Hillier. (2000). Ab initio hybrid quantum mechanical/molecular mechanical studies of the mechanisms of the enzymes protein kinase and thymidine phosphorylase. Journal of Molecular Structure THEOCHEM. 506(1-3). 35–44. 20 indexed citations
12.
Sheppard, David W., et al.. (1999). What is the mechanism of phosphoryl transfer in protein kinases? A hybrid quantum mechanical/molecular mechanical study. Chemical Communications. 79–80. 31 indexed citations
13.
Burton, Neil A., et al.. (1998). Prediction of the mechanisms of enzyme-catalysed reactions using hybrid quantum mechanical/molecular mechanical methods. Faraday Discussions. 110(110). 463–475. 35 indexed citations
14.
Hillier, Ian H., et al.. (1998). An Alternative Role for the Conserved Asp Residue in Phosphoryl Transfer Reactions. Journal of the American Chemical Society. 120(51). 13535–13536. 24 indexed citations
15.
Buess, M. L., P. J. Bray, & David W. Sheppard. (1984). 14N and 35Cl nuclear quadrupole resonance data for nitrogen mustards: Attempted correlations with chemical and biological activities. Organic Magnetic Resonance. 22(2). 67–74. 4 indexed citations
16.
Cox, R. A. & David W. Sheppard. (1982). Rate coefficient for the reaction of BrO with HO2 at 303 K. Journal of the Chemical Society Faraday Transactions 2 Molecular and Chemical Physics. 78(8). 1383–1383. 27 indexed citations
17.
Cox, R. A., et al.. (1982). Absorption coefficients and kinetics of the BrO radical using molecular modulation. Journal of Photochemistry. 19(3). 189–207. 30 indexed citations
18.
Kerr, J. A. & David W. Sheppard. (1981). Kinetics of the reactions of hydroxyl radicals with aldehydes studied under atmospheric conditions. Environmental Science & Technology. 15(8). 960–963. 74 indexed citations
19.
Sheppard, David W., et al.. (1977). A chlorine-35 nuclear quadrupole resonance study of some nitrogen mustard compounds. Journal of Magnetic Resonance (1969). 28(2). 253–257. 3 indexed citations

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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