Padmaja Dhanasekaran
- Molecular Biology top 5%
- Surgery top 5%
- Endocrinology, Diabetes and Metabolism top 2%
- Physiology top 5%
- Oncology top 10%
- Co-authors
- Michael C. PhillipsSissel Lund‐KatzHiroyuki SaitoDavid NguyenMargaret NickelGeorge H. RothblatKarl H. WeisgraberCharulatha Vedhachalam
- Topics
- Peroxisome Proliferator-Activated Receptors (23 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (18 papers)Cholesterol and Lipid Metabolism (17 papers)
- Journals
- Journal of Biological ChemistryBiochemistryArteriosclerosis Thrombosis and Vascular Biology
- Partner nations
- United StatesJapanBelgium
In The Last Decade
Padmaja Dhanasekaran
38 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 1.3k
- Surgery 1.1k
- Endocrinology, Diabetes and Metabolism 766
- Physiology 413
- Oncology 310
Countries citing papers authored by Padmaja Dhanasekaran
This map shows the geographic impact of Padmaja Dhanasekaran'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 Padmaja Dhanasekaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Padmaja Dhanasekaran more than expected).
Fields of papers citing papers by Padmaja Dhanasekaran
This network shows the impact of papers produced by Padmaja Dhanasekaran. 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 Padmaja Dhanasekaran. The network helps show where Padmaja Dhanasekaran may publish in the future.
Co-authorship network of co-authors of Padmaja Dhanasekaran
This figure shows the co-authorship network connecting the top 25 collaborators of Padmaja Dhanasekaran. A scholar is included among the top collaborators of Padmaja Dhanasekaran based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Padmaja Dhanasekaran. Padmaja Dhanasekaran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 30 | |
| 2 | 36 | |
| 3 | 28 | |
| 4 | 39 | |
| 5 | 22 | |
| 6 | 21 | |
| 7 | 33 | |
| 8 | 279 | |
| 9 | 70 | |
| 10 | 109 | |
| 11 | 74 | |
| 12 | 85 | |
| 13 | 69 | |
| 14 | 70 | |
| 15 | 110 | |
| 16 | 77 | |
| 17 | 87 | |
| 18 | 108 | |
| 19 | 49 | |
| 20 | 38 |
About Padmaja Dhanasekaran
Padmaja Dhanasekaran is a scholar working on Endocrinology, Diabetes and Metabolism, Cancer Research and Surgery, having authored 38 papers that have together received 2.2k indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (23 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (18 papers) and Cholesterol and Lipid Metabolism (17 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (766 citations), Surgery (1.1k citations) and Biochemistry (178 citations). Padmaja Dhanasekaran has collaborated with scholars based in United States, Japan and Belgium. Frequent co-authors include Michael C. Phillips, Sissel Lund‐Katz, Hiroyuki Saito, David Nguyen, Margaret Nickel, George H. Rothblat, Karl H. Weisgraber, Charulatha Vedhachalam, Masafumi Tanaka and Paul Holvoet. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry and Arteriosclerosis Thrombosis and Vascular Biology.
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.