John Bradshaw

2.3k total citations
49 papers, 1.3k citations indexed

About

John Bradshaw is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, John Bradshaw has authored 49 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 13 papers in Molecular Biology and 8 papers in Materials Chemistry. Recurrent topics in John Bradshaw's work include Computational Drug Discovery Methods (16 papers), Machine Learning in Materials Science (6 papers) and Analytical Chemistry and Chromatography (4 papers). John Bradshaw is often cited by papers focused on Computational Drug Discovery Methods (16 papers), Machine Learning in Materials Science (6 papers) and Analytical Chemistry and Chromatography (4 papers). John Bradshaw collaborates with scholars based in United Kingdom, United States and Germany. John Bradshaw's co-authors include Peter Willett, Valerie J. Gillet, Darren V. S. Green, Lesley J. Rogers, Andrew R. Leach, G. R. Pearson, T.J. Gruffydd‐Jones, John Gittins, Richard C. Holz and Brian Bennett and has published in prestigious journals such as Angewandte Chemie International Edition, Inorganic Chemistry and International Journal of Biological Macromolecules.

In The Last Decade

John Bradshaw

47 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Bradshaw United Kingdom 17 612 519 193 136 130 49 1.3k
Dimitriοs Vlachakis Greece 23 168 0.3× 1.0k 1.9× 33 0.2× 91 0.7× 82 0.6× 233 2.1k
Andreas Lange Germany 19 233 0.4× 742 1.4× 124 0.6× 54 0.4× 300 2.3× 43 2.0k
Claes Andersson Sweden 25 94 0.2× 636 1.2× 36 0.2× 175 1.3× 62 0.5× 114 1.9k
Matthias Rottmann Switzerland 27 238 0.4× 650 1.3× 25 0.1× 31 0.2× 59 0.5× 75 2.1k
W. Patrick Sullivan United States 35 244 0.4× 3.4k 6.5× 65 0.3× 489 3.6× 423 3.3× 88 5.1k
Cornelius Frömmel Germany 25 229 0.4× 1.3k 2.5× 97 0.5× 15 0.1× 419 3.2× 42 1.7k
Robert W. Myers United States 26 60 0.1× 1.4k 2.6× 49 0.3× 103 0.8× 95 0.7× 80 2.4k
M. Endres United States 25 176 0.3× 795 1.5× 13 0.1× 60 0.4× 67 0.5× 59 2.7k
Charlotte Harrison United Kingdom 19 192 0.3× 784 1.5× 21 0.1× 64 0.5× 37 0.3× 186 1.7k
Satendra Singh India 19 57 0.1× 492 0.9× 46 0.2× 49 0.4× 21 0.2× 100 1.6k

Countries citing papers authored by John Bradshaw

Since Specialization
Citations

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

Fields of papers citing papers by John Bradshaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Bradshaw

This figure shows the co-authorship network connecting the top 25 collaborators of John Bradshaw. A scholar is included among the top collaborators of John Bradshaw 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 John Bradshaw. John Bradshaw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bradshaw, John, et al.. (2025). Challenging Reaction Prediction Models to Generalize to Novel Chemistry. ACS Central Science. 11(4). 539–549. 4 indexed citations
2.
Joung, Joonyoung F., et al.. (2024). Reproducing Reaction Mechanisms with Machine‐Learning Models Trained on a Large‐Scale Mechanistic Dataset. Angewandte Chemie International Edition. 63(43). e202411296–e202411296. 5 indexed citations
3.
Joung, Joonyoung F., et al.. (2024). Reproducing Reaction Mechanisms with Machine‐Learning Models Trained on a Large‐Scale Mechanistic Dataset. Angewandte Chemie. 136(43). 1 indexed citations
4.
Bradshaw, John, Brooks Paige, Matt J. Kusner, Marwin Segler, & José Miguel Hernández-Lobato. (2020). Barking up the right tree: an approach to search over molecule synthesis DAGs. Apollo (University of Cambridge). 33. 6852–6866. 8 indexed citations
5.
Bradshaw, John, Matt J. Kusner, Brooks Paige, Marwin Segler, & José Miguel Hernández-Lobato. (2019). Generating molecules via chemical reactions. UCL Discovery (University College London). 1 indexed citations
6.
Bradshaw, John, Brooks Paige, Matt J. Kusner, Marwin Segler, & José Miguel Hernández-Lobato. (2019). A Model to Search for Synthesizable Molecules. PolyPublie (École Polytechnique de Montréal). 32. 7905–7917. 26 indexed citations
7.
Li, Yingzhen, John Bradshaw, & Yash Sharma. (2018). Are Generative Classifiers More Robust to Adversarial Attacks. arXiv (Cornell University). 3804–3814. 10 indexed citations
8.
Bradshaw, John. (2014). Cat sense : the feline enigma revealed. Penguin eBooks. 15 indexed citations
9.
Bradshaw, John. (2012). Reclaiming Virtue: How We Can Develop the Moral Intelligence to Do the Right Thing at the Right Time for the Right Reason (New York: Bantam, 2009). 32. 2 indexed citations
10.
Chen, Jenny, John D. Holliday, & John Bradshaw. (2009). A Machine Learning Approach to Weighting Schemes in the Data Fusion of Similarity Coefficients. Journal of Chemical Information and Modeling. 49(2). 185–194. 10 indexed citations
11.
Bradshaw, John, G. R. Pearson, & T.J. Gruffydd‐Jones. (2004). A Retrospective Study of 286 Cases of Neurological Disorders of the Cat. Journal of Comparative Pathology. 131(2-3). 112–120. 60 indexed citations
12.
Gillet, Valerie J., Peter Willett, & John Bradshaw. (2003). Similarity Searching Using Reduced Graphs. Journal of Chemical Information and Computer Sciences. 43(2). 338–345. 110 indexed citations
13.
Kidd, Jessica & John Bradshaw. (2002). Bilateral nonossifying fibromas in the proximal tibiae of a yearling Thoroughbred filly. Equine Veterinary Journal. 34(3). 317–320. 7 indexed citations
14.
Holz, Richard C., John Bradshaw, & Brian Bennett. (1998). Synthesis, Molecular Structure, and Reactivity of Dinuclear Copper(II) Complexes with Carboxylate-Rich Coordination Environments. Inorganic Chemistry. 37(6). 1219–1225. 42 indexed citations
15.
Gillet, Valerie J., Peter Willett, John Bradshaw, & Darren V. S. Green. (1998). Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties. Journal of Chemical Information and Computer Sciences. 39(1). 169–177. 85 indexed citations
16.
Bradshaw, John, Peter Brown, G. R. Pearson, & P. E. Holt. (1996). Dysuria associated with urethral caruncle in the dog. Journal of Comparative Pathology. 115(1). 77–84. 2 indexed citations
17.
Dunbar, Robin, John Bradshaw, & Lesley J. Rogers. (1994). The Evolution of Lateral Asymmetries, Language, Tool Use, and Intellect.. Man. 29(2). 475–475. 13 indexed citations
18.
19.
Bradshaw, John. (1987). Bradshaw on the Family: A Revolutionary Way of Self Discovery. Bulletin of Miscellaneous Information (Royal Gardens Kew). 23 indexed citations
20.
Bradshaw, John. (1974). What is Language Mastery. 1 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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