Nagaraj M. Kulkarni

507 total citations
19 papers, 410 citations indexed

About

Nagaraj M. Kulkarni is a scholar working on Epidemiology, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Nagaraj M. Kulkarni has authored 19 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Epidemiology, 7 papers in Molecular Biology and 4 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Nagaraj M. Kulkarni's work include Liver Disease Diagnosis and Treatment (7 papers), Diet, Metabolism, and Disease (4 papers) and Bioactive Compounds and Antitumor Agents (3 papers). Nagaraj M. Kulkarni is often cited by papers focused on Liver Disease Diagnosis and Treatment (7 papers), Diet, Metabolism, and Disease (4 papers) and Bioactive Compounds and Antitumor Agents (3 papers). Nagaraj M. Kulkarni collaborates with scholars based in India, United States and Sweden. Nagaraj M. Kulkarni's co-authors include B. M. Patil, R. Dhamotharan, S. Murugesan, Banappa S. Unger, Jan Borén, Margit Mahlapuu, Emmelie Cansby, Shridhar Narayanan, Manoj Amrutkar and Santosh Vishwakarma and has published in prestigious journals such as The FASEB Journal, European Journal of Pharmacology and Journal of Endocrinology.

In The Last Decade

Nagaraj M. Kulkarni

19 papers receiving 404 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nagaraj M. Kulkarni India 13 151 86 57 53 47 19 410
Sungmin Bae South Korea 12 241 1.6× 78 0.9× 40 0.7× 46 0.9× 22 0.5× 38 521
Waseem El‐Huneidi United Arab Emirates 15 257 1.7× 39 0.5× 59 1.0× 29 0.5× 28 0.6× 61 653
Lucia Dwi Antika Indonesia 12 133 0.9× 36 0.4× 28 0.5× 29 0.5× 61 1.3× 20 393
Jiwon Ahn South Korea 13 250 1.7× 92 1.1× 18 0.3× 28 0.5× 25 0.5× 26 485
Jung Yoon Jang South Korea 15 263 1.7× 87 1.0× 43 0.8× 27 0.5× 27 0.6× 22 571
Sung Ok Kim South Korea 14 244 1.6× 39 0.5× 31 0.5× 22 0.4× 46 1.0× 27 517
Qin Deng China 8 226 1.5× 91 1.1× 23 0.4× 37 0.7× 33 0.7× 13 403
Pierre S. Haddad Canada 13 275 1.8× 53 0.6× 90 1.6× 42 0.8× 41 0.9× 16 629
Naihua Hu China 9 181 1.2× 141 1.6× 47 0.8× 27 0.5× 25 0.5× 11 425
Weiling Pu China 11 286 1.9× 37 0.4× 61 1.1× 22 0.4× 48 1.0× 22 493

Countries citing papers authored by Nagaraj M. Kulkarni

Since Specialization
Citations

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

Fields of papers citing papers by Nagaraj M. Kulkarni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nagaraj M. Kulkarni. 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 Nagaraj M. Kulkarni. The network helps show where Nagaraj M. Kulkarni may publish in the future.

Co-authorship network of co-authors of Nagaraj M. Kulkarni

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

All Works

19 of 19 papers shown
1.
S, Ben Geoffrey A, et al.. (2025). Molecular Glue-Design-Evaluator (MOLDE): An Advanced Method for In-Silico Molecular Glue Design. ACS Omega. 10(7). 6650–6662. 5 indexed citations
2.
S, Ben Geoffrey A, et al.. (2024). PROTAC-Design-Evaluator (PRODE): An Advanced Method for In-Silico PROTAC Design. ACS Omega. 9(11). 12611–12621. 6 indexed citations
3.
Cansby, Emmelie, Sima Kumari, Yeshwant Kurhe, et al.. (2021). STE20‐Type Protein Kinase MST4 Controls NAFLD Progression by Regulating Lipid Droplet Dynamics and Metabolic Stress in Hepatocytes. Hepatology Communications. 5(7). 1183–1200. 13 indexed citations
4.
Cansby, Emmelie, Lei Gao, Nagaraj M. Kulkarni, et al.. (2020). Depletion of protein kinase STK25 ameliorates renal lipotoxicity and protects against diabetic kidney disease. JCI Insight. 5(24). 14 indexed citations
5.
Kulkarni, Nagaraj M., et al.. (2020). High fat worsens olanzapine induced metabolic abnormalities in rats. British Food Journal. 122(10). 3065–3075. 1 indexed citations
6.
Cansby, Emmelie, Nagaraj M. Kulkarni, Yeshwant Kurhe, et al.. (2019). Protein kinase MST3 modulates lipid homeostasis in hepatocytes and correlates with nonalcoholic steatohepatitis in humans. The FASEB Journal. 33(9). 9974–9989. 24 indexed citations
7.
Cansby, Emmelie, Esther Nuñez‐Durán, Manoj Amrutkar, et al.. (2018). Targeted Delivery of Stk25 Antisense Oligonucleotides to Hepatocytes Protects Mice Against Nonalcoholic Fatty Liver Disease. Cellular and Molecular Gastroenterology and Hepatology. 7(3). 597–618. 37 indexed citations
8.
Sütt, Silva, Emmelie Cansby, Alexandra Paul, et al.. (2018). STK25 regulates oxidative capacity and metabolic efficiency in adipose tissue. Journal of Endocrinology. 238(3). 187–202. 15 indexed citations
9.
10.
Kulkarni, Nagaraj M., et al.. (2017). Terminalia chebula Retz. – an important medicinal plant. Herba Polonica. 63(4). 45–56. 20 indexed citations
11.
Kulkarni, Nagaraj M., Sandeep Malampati, S. Chandrasekaran, et al.. (2016). Altered pharmacokinetics of rosiglitazone in a mouse model of non-alcoholic fatty liver disease. Drug Metabolism and Personalized Therapy. 31(3). 165–171. 10 indexed citations
12.
Chandrasekhar, K. B., et al.. (2015). Phosphodiesterase inhibitor, pentoxifylline enhances anticancer activity of histone deacetylase inhibitor, MS-275 in human breast cancer in vitro and in vivo. European Journal of Pharmacology. 764. 508–519. 15 indexed citations
13.
Kulkarni, Nagaraj M., et al.. (2014). A novel animal model of metabolic syndrome with non-alcoholic fatty liver disease and skin inflammation. Pharmaceutical Biology. 53(8). 1110–1117. 16 indexed citations
14.
Kulkarni, Nagaraj M., et al.. (2014). Topical atorvastatin ameliorates 12-O-tetradecanoylphorbol-13-acetate induced skin inflammation by reducing cutaneous cytokine levels and NF-κB activation. Archives of Pharmacal Research. 38(6). 1238–1247. 21 indexed citations
15.
De, Soumita, et al.. (2014). Combination of vildagliptin and rosiglitazone ameliorates nonalcoholic fatty liver disease in C57BL/6 mice. Indian Journal of Pharmacology. 46(1). 46–46. 6 indexed citations
16.
Dhamotharan, R., et al.. (2011). Embelin reduces cutaneous TNF-α level and ameliorates skin edema in acute and chronic model of skin inflammation in mice. European Journal of Pharmacology. 662(1-3). 63–69. 71 indexed citations
17.
Kulkarni, Nagaraj M., et al.. (2011). Embelin ameliorates dextran sodium sulfate-induced colitis in mice. International Immunopharmacology. 11(6). 724–731. 57 indexed citations
18.
Kulkarni, Nagaraj M., et al.. (2010). Modulation of the cyclooxygenase pathway via inhibition of nitric oxide production contributes to the anti-inflammatory activity of kaempferol. European Journal of Pharmacology. 642(1-3). 169–176. 42 indexed citations
19.
Patil, B. M., Nagaraj M. Kulkarni, & Banappa S. Unger. (2006). Elevation of systolic blood pressure in an animal model of olanzapine induced weight gain. European Journal of Pharmacology. 551(1-3). 112–115. 31 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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