Angelo Pugliese

1.5k citations
23 papers · 1.1k indexed · h-index 16

Impact in

Papers in

Angelo Pugliese

23 papers receiving 1.1k citations

Peers

Angelo Pugliese
Comparison fields: 5 of 102
  • Biochemistry 124
  • Pharmacology 136
  • Geriatrics and Gerontology 57
  • Computational Theory and Mathematics 211
  • Applied Microbiology and Biotechnology 21
Replace Do Young Lim with:
Do Young Lim United States
Yong-Seok Heo South Korea
Stefania Bilotto Italy
Govindaraj Sharmila India
Ean‐Jeong Seo Germany
Ramamurthi Vidya Priyadarsini India
Naomi Oi United States
Yih Ho Taiwan
Masayoshi Oyama Japan
Bianca M. Liederer United States
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Citations per field
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Citations per year

Countries citing papers authored by Angelo Pugliese

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Angelo Pugliese Line = papers co-authored together Angelo Pugliese links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20233
2 20221
3 201930
4 20182
5 201515
6 2013129
7 201235
8 201229
9 2011117
10 20111
11 201079
12 201052
13 201041
14 201020
15 2009149
16 200958
17 200854
18 200820
19 200886
20 2008159

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.

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