Stephen C. Pak
Impact in
- Aging top 0.5%
- Genetics, Aging, and Longevity in Model Organisms
- Cancer Research top 5%
- Protease and Inhibitor Mechanisms
Papers in
-
- Mitochondrial Function and Pathology 6
- Signaling Pathways in Disease 5
- CRISPR and Genetic Engineering 4
- Aging 23
- Genetics, Aging, and Longevity in Model Organisms 23
- Co-authors
- Gary A. Silverman (46 shared papers)Cliff J. Luke (28 shared papers)David H. Perlmutter (15 shared papers)Linda P. O’Reilly (10 shared papers)James C. Whisstock (6 shared papers)David J. Askew (7 shared papers)Phillip I. Bird (4 shared papers)David H. Perlmutter (8 shared papers)
- Journals
- Journal of Biological Chemistry (7 papers)PLoS ONE (6 papers)Biochemistry (4 papers)Human Molecular Genetics (2 papers)Molecular Genetics and Metabolism (2 papers)
- Partner nations
- United StatesAustraliaFrance
In The Last Decade
Stephen C. Pak
52 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 114
- Aging 412
- Cancer Research 427
- Cell Biology 291
- Parasitology 88
- Molecular Biology 846
Countries citing papers authored by Stephen C. Pak
This map shows the geographic impact of Stephen C. Pak'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 Stephen C. Pak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen C. Pak more than expected).
Fields of papers citing papers by Stephen C. Pak
This network shows the impact of papers produced by Stephen C. Pak. 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 Stephen C. Pak. The network helps show where Stephen C. Pak may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen C. Pak, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 192 | |
| 2 | 2004 | 150 | |
| 3 | 2010 | 135 | |
| 4 | 2007 | 132 | |
| 5 | 2010 | 126 | |
| 6 | 2010 | 92 | |
| 7 | 2008 | 75 | |
| 8 | 2000 | 63 | |
| 9 | 2022 | 56 | |
| 10 | 2017 | 55 | |
| 11 | 2021 | 49 | |
| 12 | 2002 | 47 | |
| 13 | 2002 | 47 | |
| 14 | 2001 | 43 | |
| 15 | 2000 | 39 | |
| 16 | 2012 | 36 | |
| 17 | 2004 | 35 | |
| 18 | 2014 | 34 | |
| 19 | 2014 | 34 | |
| 20 | 2017 | 33 |
About Stephen C. Pak
Stephen C. Pak is a scholar working on Molecular Biology, Aging, Cancer Research, Cell Biology and Epidemiology, having authored 53 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (23 papers), Protease and Inhibitor Mechanisms (15 papers), Cellular transport and secretion (7 papers), Endoplasmic Reticulum Stress and Disease (6 papers), Mitochondrial Function and Pathology (6 papers), Signaling Pathways in Disease (5 papers), Autophagy in Disease and Therapy (5 papers) and CRISPR and Genetic Engineering (4 papers). The work is most often cited by research in Aging (412 citations), Cancer Research (427 citations), Cell Biology (291 citations), Parasitology (88 citations) and Molecular Biology (846 citations). Stephen C. Pak has collaborated with scholars based in United States, Australia and France. Frequent co-authors include Gary A. Silverman, Cliff J. Luke, David H. Perlmutter, Linda P. O’Reilly, James C. Whisstock, David J. Askew, Phillip I. Bird, David H. Perlmutter, Olivia S. Long and Sule Çataltepe. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE, Biochemistry, Human Molecular Genetics and Molecular Genetics and Metabolism.
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.