Jonathan Lippy
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 10%
- Cholinesterase and Neurodegenerative Diseases
Papers in
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- Protein Degradation and Inhibitors 3
- Receptor Mechanisms and Signaling 3
- Cell death mechanisms and regulation 2
- Single-cell and spatial transcriptomics 2
- Wnt/β-catenin signaling in development and cancer 2
- Oncology 9
- Cytokine Signaling Pathways and Interactions 3
- Co-authors
- George L. Trainor (5 shared papers)H.A. Lewis (2 shared papers)Kevin Kish (2 shared papers)Carol Krause (2 shared papers)Hong Xiao (2 shared papers)Gene M. Dubowchik (2 shared papers)John E. Macor (2 shared papers)Prasanna Sivaprakasam (2 shared papers)
- Journals
- Bioorganic & Medicinal Chemistry Letters (8 papers)SLAS DISCOVERY (6 papers)Analytical Biochemistry (4 papers)Journal of Medicinal Chemistry (2 papers)Drug Discovery Today (2 papers)
- Partner nations
- United StatesGermanySweden
In The Last Decade
Jonathan Lippy
25 papers receiving 510 citations
Peers
Comparison fields: 5 of 73
- Computational Theory and Mathematics 121
- Pharmacology 95
- Molecular Biology 353
- Organic Chemistry 130
- Genetics 38
Countries citing papers authored by Jonathan Lippy
This map shows the geographic impact of Jonathan Lippy'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 Jonathan Lippy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Lippy more than expected).
Fields of papers citing papers by Jonathan Lippy
This network shows the impact of papers produced by Jonathan Lippy. 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 Jonathan Lippy. The network helps show where Jonathan Lippy may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan Lippy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 106 | |
| 2 | 2010 | 64 | |
| 3 | 2016 | 59 | |
| 4 | 2000 | 47 | |
| 5 | 2012 | 29 | |
| 6 | 2015 | 23 | |
| 7 | 2007 | 20 | |
| 8 | 2012 | 19 | |
| 9 | 2001 | 16 | |
| 10 | 2010 | 16 | |
| 11 | 2007 | 15 | |
| 12 | 2000 | 13 | |
| 13 | 2015 | 13 | |
| 14 | 2018 | 12 | |
| 15 | 2014 | 11 | |
| 16 | 2015 | 10 | |
| 17 | 2017 | 10 | |
| 18 | 2019 | 9 | |
| 19 | 2012 | 8 | |
| 20 | 2018 | 6 |
About Jonathan Lippy
Jonathan Lippy is a scholar working on Molecular Biology, Oncology, Computational Theory and Mathematics, Genetics and Immunology, having authored 25 papers that have together received 529 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Protein Degradation and Inhibitors (3 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), Receptor Mechanisms and Signaling (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Cell death mechanisms and regulation (2 papers), Single-cell and spatial transcriptomics (2 papers) and Wnt/β-catenin signaling in development and cancer (2 papers). The work is most often cited by research in Computational Theory and Mathematics (121 citations), Pharmacology (95 citations), Molecular Biology (353 citations), Organic Chemistry (130 citations) and Genetics (38 citations). Jonathan Lippy has collaborated with scholars based in United States, Germany and Sweden. Frequent co-authors include George L. Trainor, H.A. Lewis, Kevin Kish, Carol Krause, Hong Xiao, Gene M. Dubowchik, John E. Macor, Prasanna Sivaprakasam, David R. Langley and Catherine R. Burton. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, SLAS DISCOVERY, Analytical Biochemistry, Journal of Medicinal Chemistry and Drug Discovery Today.
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.