Jon Chambers
- Computational Theory and Mathematics top 0.05%
- Computational Drug Discovery Methods 9
- Endocrine and Autonomic Systems top 0.5%
- Regulation of Appetite and Obesity 3
- Physiology top 0.5%
- Adenosine and Purinergic Signaling 4
- Pharmacology top 0.5%
- Microbial Natural Products and Biosynthesis 3
- Molecular Biology top 1%
- Receptor Mechanisms and Signaling 7
- Metabolomics and Mass Spectrometry Studies 3
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- Neuropeptides and Animal Physiology 4
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- Chemokine receptors and signaling 3
- Co-authors
- John P. OveringtonAnna GaultonAnne HerseyMark DaviesLouisa J. BellisA. Patrícia BentoYvonne LightBissan Al‐Lazikani
- Journals
- Nucleic Acids Research (4 papers)Journal of Biological Chemistry (3 papers)Journal of Cheminformatics (2 papers)
- Partner nations
- United KingdomUnited StatesNew Zealand
In The Last Decade
Jon Chambers
22 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Computational Theory and Mathematics 4.3k
- Endocrine and Autonomic Systems 785
- Physiology 381
- Pharmacology 1.4k
- Molecular Biology 4.8k
Countries citing papers authored by Jon Chambers
This map shows the geographic impact of Jon Chambers'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 Jon Chambers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Chambers more than expected).
Fields of papers citing papers by Jon Chambers
This network shows the impact of papers produced by Jon Chambers. 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 Jon Chambers. The network helps show where Jon Chambers may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jon Chambers, 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 | 2023 | 4 | |
| 2 | The ChEMBL database in 2017breakdown → | 2016 | 1589 |
| 3 | 2015 | 150 | |
| 4 | 2015 | 34 | |
| 5 | 2014 | 24 | |
| 6 | The ChEMBL bioactivity database: an updatebreakdown → | 2013 | 1117 |
| 7 | 2013 | 115 | |
| 8 | ChEMBL: a large-scale bioactivity database for drug discoverybreakdown → | 2011 | 2947 |
| 9 | 2002 | 14 | |
| 10 | 2001 | 68 | |
| 11 | 2001 | 186 | |
| 12 | 2001 | 122 | |
| 13 | 2000 | 126 | |
| 14 | The endogenous lipid anandamide is a full agonist at the human vanilloid receptor (hVR1)breakdown → | 2000 | 637 |
| 15 | 2000 | 56 | |
| 16 | 2000 | 226 | |
| 17 | 2000 | 145 | |
| 18 | 1999 | 12 | |
| 19 | 1999 | 286 | |
| 20 | 1999 | 413 |
About Jon Chambers
Jon Chambers is a scholar working on Physiology, Endocrine and Autonomic Systems and Computational Theory and Mathematics, having authored 22 papers that have together received 8.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Receptor Mechanisms and Signaling (7 papers), Adenosine and Purinergic Signaling (4 papers), Neuropeptides and Animal Physiology (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Microbial Natural Products and Biosynthesis (3 papers), Chemokine receptors and signaling (3 papers) and Regulation of Appetite and Obesity (3 papers). The work is most often cited by research in Computational Theory and Mathematics (4.3k citations), Endocrine and Autonomic Systems (785 citations) and Physiology (381 citations). Jon Chambers has collaborated with scholars based in United Kingdom, United States and New Zealand. Frequent co-authors include John P. Overington, Anna Gaulton, Anne Hersey, Mark Davies, Louisa J. Bellis, A. Patrícia Bento, Yvonne Light, Bissan Al‐Lazikani, David Michalovich and George Papadatos. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry, Journal of Cheminformatics, Molecular Pharmacology and Nature.
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.