Maya S. Gowri

536 total citations
10 papers, 450 citations indexed

About

Maya S. Gowri is a scholar working on Physiology, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Maya S. Gowri has authored 10 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Physiology, 4 papers in Molecular Biology and 3 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Maya S. Gowri's work include Peroxisome Proliferator-Activated Receptors (4 papers), Adipose Tissue and Metabolism (3 papers) and Antioxidant Activity and Oxidative Stress (3 papers). Maya S. Gowri is often cited by papers focused on Peroxisome Proliferator-Activated Receptors (4 papers), Adipose Tissue and Metabolism (3 papers) and Antioxidant Activity and Oxidative Stress (3 papers). Maya S. Gowri collaborates with scholars based in United States. Maya S. Gowri's co-authors include Deneys R. van der Westhuyzen, James W. Anderson, Michele Mietus‐Snyder, Robert E. Pitas, Gerald M. Reaven, James W. Anderson, James W. Anderson, Peter R. Oeltgen, Laura Nichols and Jan R. Turner and has published in prestigious journals such as Journal of Biological Chemistry, Arteriosclerosis Thrombosis and Vascular Biology and American Journal of Physiology-Endocrinology and Metabolism.

In The Last Decade

Maya S. Gowri

10 papers receiving 430 citations

Peers

Maya S. Gowri

EDM

SURGE

BIOCH

EPIDE

Kazuo Kotani Japan

Tadateru Hamada Japan

Juan A. Monti Argentina

Marı́a Cristina Carrillo Argentina

María Alonso-Chamorro Spain

Zhanfang Kang China

Wim Verreth Belgium

Nair Seiko Yamamoto Brazil

Barbara Buchetti Italy

M. J. Lee South Korea

Kazuo Kotani Japan

Maya S. Gowri

146 ×0.9

EDM

163 ×1.3

247 ×2.5

SURGE

148 ×1.8

BIOCH

87 ×1.2

EPIDE

Citations per year, relative to Maya S. Gowri Maya S. Gowri (= 1×) peers Kazuo Kotani

Countries citing papers authored by Maya S. Gowri

Since Specialization

Citations

This map shows the geographic impact of Maya S. Gowri'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 Maya S. Gowri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya S. Gowri more than expected).

Fields of papers citing papers by Maya S. Gowri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya S. Gowri. 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 Maya S. Gowri. The network helps show where Maya S. Gowri may publish in the future.

Co-authorship network of co-authors of Maya S. Gowri

This figure shows the co-authorship network connecting the top 25 collaborators of Maya S. Gowri. A scholar is included among the top collaborators of Maya S. Gowri 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 Maya S. Gowri. Maya S. Gowri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Medicherla, Satya, Partha Neogi, Maya S. Gowri, et al.. (2003). A novel peroxisome proliferator-activated gamma (PPARγ) agonist, CLX-0921, has potent antihyperglycemic activity with low adipogenic potential. Metabolism. 52(8). 1012–1018. 20 indexed citations

Neogi, Partha, Satyanarayana Medicherla, Jin Q. Cheng, et al.. (2003). Synthesis and structure–Activity relationship studies of cinnamic acid-based novel thiazolidinedione antihyperglycemic agents. Bioorganic & Medicinal Chemistry. 11(18). 4059–4067. 46 indexed citations

Scribner, Karen A., et al.. (2000). Masoprocol decreases serum triglyceride concentrations in rats with fructose-induced hypertriglyceridemia. Metabolism. 49(9). 1106–1110. 21 indexed citations

Mietus‐Snyder, Michele, Maya S. Gowri, & Robert E. Pitas. (2000). Class A Scavenger Receptor Up-regulation in Smooth Muscle Cells by Oxidized Low Density Lipoprotein. Journal of Biological Chemistry. 275(23). 17661–17670. 88 indexed citations

Gowri, Maya S., et al.. (2000). Masoprocol decreases rat lipolytic activity by decreasing the phosphorylation of HSL. American Journal of Physiology-Endocrinology and Metabolism. 279(3). E593–E600. 15 indexed citations

Gowri, Maya S., Gerald M. Reaven, & Salman Azhar. (1999). Effect of masoprocol on glucose transport and lipolysis by isolated rat adipocytes. Metabolism. 48(4). 411–414. 12 indexed citations

Anderson, James W., Maya S. Gowri, Jan R. Turner, et al.. (1999). Antioxidant Supplementation Effects on Low-Density Lipoprotein Oxidation for Individuals with Type 2 Diabetes Mellitus. Journal of the American College of Nutrition. 18(5). 451–461. 56 indexed citations

Anderson, James W., et al.. (1999). Postprandial Low‐Density Lipoproteins in Type 2 Diabetes are Oxidized More Extensively Than Fasting Diabetes and Control Samples. Proceedings of The Society for Experimental Biology and Medicine. 222(2). 178–184. 47 indexed citations

Gowri, Maya S.. (1999). Masoprocol lowers blood pressure in rats with fructose-induced hypertension. American Journal of Hypertension. 12(7). 744–746. 9 indexed citations

10.

Gowri, Maya S., et al.. (1999). Decreased Protection by HDL From Poorly Controlled Type 2 Diabetic Subjects Against LDL Oxidation May Be Due to the Abnormal Composition of HDL. Arteriosclerosis Thrombosis and Vascular Biology. 19(9). 2226–2233. 136 indexed citations

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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