Angelo Pugliese
Impact in
- Biochemistry top 5%
- Phytochemicals and Antioxidant Activities
- Pharmacology top 5%
- Ginger and Zingiberaceae research
Papers in
-
- Sirtuins and Resveratrol in Medicine 3
-
- Pharmacogenetics and Drug Metabolism 3
- Co-authors
- Zigang DongAnn M. BodeYong‐Yeon ChoMarc C. NicklausMarkus SitzmannChul‐Ho JeongChenzhong LiaoJung‐Hyun Shim
- Journals
- Cancer Research (7 papers)Journal of Biological Chemistry (3 papers)Future Medicinal Chemistry (3 papers)Bioorganic & Medicinal Chemistry Letters (2 papers)Journal of Chemical Information and Modeling (1 paper)
- Partner nations
- United StatesUnited KingdomSouth Korea
In The Last Decade
Angelo Pugliese
23 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 102
- Biochemistry 124
- Pharmacology 136
- Geriatrics and Gerontology 57
- Computational Theory and Mathematics 211
- Applied Microbiology and Biotechnology 21
Countries citing papers authored by Angelo Pugliese
This map shows the geographic impact of Angelo Pugliese'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 Angelo Pugliese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angelo Pugliese more than expected).
Fields of papers citing papers by Angelo Pugliese
This network shows the impact of papers produced by Angelo Pugliese. 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 Angelo Pugliese. The network helps show where Angelo Pugliese may publish in the future.
Co-authors
The 25 scholars most cited alongside Angelo Pugliese, 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 | 3 | |
| 2 | 2022 | 1 | |
| 3 | 2019 | 30 | |
| 4 | 2018 | 2 | |
| 5 | 2015 | 15 | |
| 6 | 2013 | 129 | |
| 7 | 2012 | 35 | |
| 8 | 2012 | 29 | |
| 9 | 2011 | 117 | |
| 10 | 2011 | 1 | |
| 11 | 2010 | 79 | |
| 12 | 2010 | 52 | |
| 13 | 2010 | 41 | |
| 14 | 2010 | 20 | |
| 15 | 2009 | 149 | |
| 16 | 2009 | 58 | |
| 17 | 2008 | 54 | |
| 18 | 2008 | 20 | |
| 19 | 2008 | 86 | |
| 20 | 2008 | 159 |
About Angelo Pugliese
Angelo Pugliese is a scholar working on Geriatrics and Gerontology, Pharmacology, Applied Microbiology and Biotechnology, Computational Theory and Mathematics and Information Systems and Management, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Machine Learning in Materials Science (3 papers), Sirtuins and Resveratrol in Medicine (3 papers), Pharmacogenetics and Drug Metabolism (3 papers), Melanoma and MAPK Pathways (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and Genomics, phytochemicals, and oxidative stress (2 papers). The work is most often cited by research in Biochemistry (124 citations), Pharmacology (136 citations), Geriatrics and Gerontology (57 citations), Computational Theory and Mathematics (211 citations) and Applied Microbiology and Biotechnology (21 citations). Angelo Pugliese has collaborated with scholars based in United States, United Kingdom and South Korea. Frequent co-authors include Zigang Dong, Ann M. Bode, Yong‐Yeon Cho, Marc C. Nicklaus, Markus Sitzmann, Chul‐Ho Jeong, Chenzhong Liao, Jung‐Hyun Shim, Ke Yao and Nam Joo Kang. Their work appears in journals such as Cancer Research, Journal of Biological Chemistry, Future Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters and Journal of Chemical Information and Modeling.
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.