Deborah Szalkowski
Impact in
- Physiology top 2%
- Adipose Tissue and Metabolism
- Biochemistry top 2%
- Lipid metabolism and biosynthesis
Papers in
-
- Metabolism, Diabetes, and Cancer 7
- Peroxisome Proliferator-Activated Receptors 7
- Protein Kinase Regulation and GTPase Signaling 3
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- Adipose Tissue and Metabolism 5
- Co-authors
- David E. Moller (10 shared papers)Bei B. Zhang (10 shared papers)J Berger (3 shared papers)Margaret Wu (5 shared papers)Joel P. Berger (2 shared papers)Thomas W. Doebber (5 shared papers)N. Berger (2 shared papers)Bing Zhang (2 shared papers)
- Journals
- Journal of Biological Chemistry (4 papers)Journal of Clinical Investigation (3 papers)Endocrinology (3 papers)Molecular Endocrinology (2 papers)Diabetes (1 paper)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Deborah Szalkowski
20 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 93
- Physiology 701
- Biochemistry 196
- Endocrine and Autonomic Systems 168
- Endocrinology, Diabetes and Metabolism 371
- Epidemiology 578
Countries citing papers authored by Deborah Szalkowski
This map shows the geographic impact of Deborah Szalkowski'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 Deborah Szalkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deborah Szalkowski more than expected).
Fields of papers citing papers by Deborah Szalkowski
This network shows the impact of papers produced by Deborah Szalkowski. 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 Deborah Szalkowski. The network helps show where Deborah Szalkowski may publish in the future.
Co-authors
The 25 scholars most cited alongside Deborah Szalkowski, 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 | 1999 | 384 | |
| 2 | 1996 | 283 | |
| 3 | 1996 | 246 | |
| 4 | 2005 | 232 | |
| 5 | 2005 | 213 | |
| 6 | 1996 | 166 | |
| 7 | 1995 | 158 | |
| 8 | 1999 | 138 | |
| 9 | 2003 | 108 | |
| 10 | 2002 | 97 | |
| 11 | 2000 | 77 | |
| 12 | 2000 | 60 | |
| 13 | 1995 | 56 | |
| 14 | 1994 | 53 | |
| 15 | 1994 | 36 | |
| 16 | 2004 | 32 | |
| 17 | 2004 | 25 | |
| 18 | 2002 | 23 | |
| 19 | 2000 | 15 | |
| 20 | 2005 | 3 |
About Deborah Szalkowski
Deborah Szalkowski is a scholar working on Molecular Biology, Physiology, Surgery, Epidemiology and Cancer Research, having authored 20 papers that have together received 2.4k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (7 papers), Peroxisome Proliferator-Activated Receptors (7 papers), Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (5 papers), Cancer, Lipids, and Metabolism (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Fatty Acid Research and Health (2 papers) and Cholesterol and Lipid Metabolism (2 papers). The work is most often cited by research in Physiology (701 citations), Biochemistry (196 citations), Endocrine and Autonomic Systems (168 citations), Endocrinology, Diabetes and Metabolism (371 citations) and Epidemiology (578 citations). Deborah Szalkowski has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include David E. Moller, Bei B. Zhang, J Berger, Margaret Wu, Joel P. Berger, Thomas W. Doebber, N. Berger, Bing Zhang, Qing Dallas-Yang and Guoqiang Jiang. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation, Endocrinology, Molecular Endocrinology and Diabetes.
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.