Suzanne Skolnik
Impact in
- Pharmaceutical Science top 5%
- Drug Solubulity and Delivery Systems
- Advanced Drug Delivery Systems
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- Computational Drug Discovery Methods
Papers in
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- Drug Solubulity and Delivery Systems 6
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- Computational Drug Discovery Methods 6
- Co-authors
- Jianling Wang (5 shared papers)Xuena Lin (3 shared papers)Jianling Wang (1 shared paper)Bailin Zhang (1 shared paper)Timothy He (1 shared paper)Wenzhan Yang (1 shared paper)Peter Gedeck (3 shared papers)Stephane Rodde (3 shared papers)
- Journals
- Journal of Chemical Information and Modeling (3 papers)Journal of Pharmaceutical Sciences (2 papers)Chemistry & Biodiversity (1 paper)The FASEB Journal (1 paper)Drug Discovery Today (1 paper)
- Partner nations
- SwitzerlandUnited StatesChina
In The Last Decade
Suzanne Skolnik
12 papers receiving 352 citations
Peers
Comparison fields: 5 of 80
- Pharmaceutical Science 64
- Computational Theory and Mathematics 112
- Pharmacology 41
- Oncology 98
- Filtration and Separation 8
Countries citing papers authored by Suzanne Skolnik
This map shows the geographic impact of Suzanne Skolnik'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 Suzanne Skolnik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suzanne Skolnik more than expected).
Fields of papers citing papers by Suzanne Skolnik
This network shows the impact of papers produced by Suzanne Skolnik. 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 Suzanne Skolnik. The network helps show where Suzanne Skolnik may publish in the future.
Co-authors
The 25 scholars most cited alongside Suzanne Skolnik, 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 | 2010 | 107 | |
| 2 | 2010 | 60 | |
| 3 | 2022 | 47 | |
| 4 | 2009 | 45 | |
| 5 | 2019 | 31 | |
| 6 | 2015 | 13 | |
| 7 | 2022 | 13 | |
| 8 | 2017 | 11 | |
| 9 | 2013 | 11 | |
| 10 | 2010 | 10 | |
| 11 | 2017 | 7 | |
| 12 | 2012 | 2 | |
| 13 | 2023 | 0 |
About Suzanne Skolnik
Suzanne Skolnik is a scholar working on Pharmaceutical Science, Computational Theory and Mathematics, Oncology, Molecular Biology and Materials Chemistry, having authored 13 papers that have together received 357 indexed citations. Recurring topics across this work include Drug Solubulity and Delivery Systems (6 papers), Computational Drug Discovery Methods (6 papers), Drug Transport and Resistance Mechanisms (5 papers), Analytical Chemistry and Chromatography (3 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Pharmacological Effects and Toxicity Studies (2 papers), Free Radicals and Antioxidants (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Pharmaceutical Science (64 citations), Computational Theory and Mathematics (112 citations), Pharmacology (41 citations), Oncology (98 citations) and Filtration and Separation (8 citations). Suzanne Skolnik has collaborated with scholars based in Switzerland, United States and China. Frequent co-authors include Jianling Wang, Xuena Lin, Jianling Wang, Bailin Zhang, Timothy He, Wenzhan Yang, Peter Gedeck, Stephane Rodde, Stephanie Dodd and Weiping Jia. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Pharmaceutical Sciences, Chemistry & Biodiversity, The FASEB Journal 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.