Jonathan E. Schneeweis
Impact in
-
- Computational Drug Discovery Methods
- Spectroscopy top 10%
- Analytical Chemistry and Chromatography
Papers in
- Oncology 3
- Cytokine Signaling Pathways and Interactions 3
- Co-authors
- Michael Shevlin (1 shared paper)Louis‐Charles Campeau (1 shared paper)Kevin P. Bateman (1 shared paper)Philippe G. Nantermet (1 shared paper)Tim Cernak (1 shared paper)A. Buitrago Santanilla (1 shared paper)Zhicai Shi (1 shared paper)Roy Helmy (1 shared paper)
- Journals
- Assay and Drug Development Technologies (3 papers)SLAS DISCOVERY (3 papers)SLAS TECHNOLOGY (1 paper)Journal of Lipid Research (1 paper)Science (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Jonathan E. Schneeweis
9 papers receiving 621 citations
Jonathan E. Schneeweis's Hit Papers
Peers
Comparison fields: 5 of 77
- Computational Theory and Mathematics 105
- Spectroscopy 101
- Organic Chemistry 167
- Biomedical Engineering 245
- Inorganic Chemistry 52
Countries citing papers authored by Jonathan E. Schneeweis
This map shows the geographic impact of Jonathan E. Schneeweis'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 E. Schneeweis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan E. Schneeweis more than expected).
Fields of papers citing papers by Jonathan E. Schneeweis
This network shows the impact of papers produced by Jonathan E. Schneeweis. 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 E. Schneeweis. The network helps show where Jonathan E. Schneeweis may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan E. Schneeweis, 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 | Nanomole-scale high-throughput chemistry for the synthesis of complex molecules Hit paper breakdown → | 2014 | 470 |
| 2 | 2006 | 41 | |
| 3 | 2008 | 37 | |
| 4 | 2003 | 26 | |
| 5 | 2004 | 26 | |
| 6 | 2006 | 19 | |
| 7 | 2015 | 12 | |
| 8 | 2020 | 6 | |
| 9 | 2005 | 4 |
About Jonathan E. Schneeweis
Jonathan E. Schneeweis is a scholar working on Molecular Biology, Oncology, Cellular and Molecular Neuroscience, Genetics and Biomedical Engineering, having authored 9 papers that have together received 641 indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (3 papers), Estrogen and related hormone effects (2 papers), Metabolism and Genetic Disorders (1 paper), Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper), Diabetes Management and Research (1 paper), Computational Drug Discovery Methods (1 paper), Bacteriophages and microbial interactions (1 paper) and Neuropeptides and Animal Physiology (1 paper). The work is most often cited by research in Computational Theory and Mathematics (105 citations), Spectroscopy (101 citations), Organic Chemistry (167 citations), Biomedical Engineering (245 citations) and Inorganic Chemistry (52 citations). Jonathan E. Schneeweis has collaborated with scholars based in United States and Japan. Frequent co-authors include Michael Shevlin, Louis‐Charles Campeau, Kevin P. Bateman, Philippe G. Nantermet, Tim Cernak, A. Buitrago Santanilla, Zhicai Shi, Roy Helmy, Simon Berritt and Erik L. Regalado. Their work appears in journals such as Assay and Drug Development Technologies, SLAS DISCOVERY, SLAS TECHNOLOGY, Journal of Lipid Research and Science.
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.