Saravanan Natarajan

550 total citations
9 papers, 412 citations indexed

About

Saravanan Natarajan is a scholar working on Nutrition and Dietetics, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Saravanan Natarajan has authored 9 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Nutrition and Dietetics, 3 papers in Infectious Diseases and 3 papers in Molecular Biology. Recurrent topics in Saravanan Natarajan's work include Fatty Acid Research and Health (4 papers), Tuberculosis Research and Epidemiology (3 papers) and Computational Drug Discovery Methods (2 papers). Saravanan Natarajan is often cited by papers focused on Fatty Acid Research and Health (4 papers), Tuberculosis Research and Epidemiology (3 papers) and Computational Drug Discovery Methods (2 papers). Saravanan Natarajan collaborates with scholars based in India, Iran and Vietnam. Saravanan Natarajan's co-authors include Ahamed Ibrahim, Ghafoorunissa, Nasreen Z. Ehtesham, Abdul Haseeb, Srikanth Tripathy, Chandrasekaran Padmapriyadarsini, Ramalingam Bethunaickan, Sudha Ramaiah, Sravan Kumar Miryala and Reetika Debroy and has published in prestigious journals such as Frontiers in Immunology, Metabolism and Journal of Molecular Liquids.

In The Last Decade

Saravanan Natarajan

9 papers receiving 388 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saravanan Natarajan India 6 175 109 107 96 88 9 412
Dawn M. Fedor United States 9 241 1.4× 128 1.2× 134 1.3× 108 1.1× 118 1.3× 18 494
Sylvia Keller Germany 15 116 0.7× 127 1.2× 186 1.7× 107 1.1× 178 2.0× 19 699
Yasuhiro Nishizaki Japan 14 58 0.3× 181 1.7× 97 0.9× 61 0.6× 153 1.7× 83 597
A Lozano Spain 12 169 1.0× 109 1.0× 89 0.8× 49 0.5× 74 0.8× 22 617
Hongyi Cai United States 16 63 0.4× 170 1.6× 118 1.1× 70 0.7× 259 2.9× 36 672
Rojeet Shrestha Japan 15 45 0.3× 68 0.6× 55 0.5× 72 0.8× 290 3.3× 46 625
Ryosuke Sato Japan 8 143 0.8× 39 0.4× 32 0.3× 53 0.6× 138 1.6× 27 477
Pezhman Alavine­jad Iran 13 68 0.4× 203 1.9× 102 1.0× 80 0.8× 103 1.2× 56 526
Shuying S. Li United States 14 79 0.5× 131 1.2× 62 0.6× 39 0.4× 266 3.0× 17 714
Antonio Sircana Italy 7 36 0.2× 119 1.1× 104 1.0× 122 1.3× 195 2.2× 8 410

Countries citing papers authored by Saravanan Natarajan

Since Specialization
Citations

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

Fields of papers citing papers by Saravanan Natarajan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Saravanan Natarajan. 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 Saravanan Natarajan. The network helps show where Saravanan Natarajan may publish in the future.

Co-authorship network of co-authors of Saravanan Natarajan

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

All Works

9 of 9 papers shown
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Kalashikam, Rajender Rao, et al.. (2022). Effect of different dietary fats on inflammation and glucose intolerance in high fructose and high fat fed experimental animals. Hormone Molecular Biology and Clinical Investigation. 43(3). 307–314. 3 indexed citations
3.
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Ahmed, N. Zaheer, Seema Akbar, Syed Hissar, et al.. (2021). Effects of co-administration of Unani pharmacopoeia formulations Qurs Tabasheer Sartani and Arq Hara Bhara with CAT-I antitubercular drugs in rats. Journal of Complementary and Integrative Medicine. 18(3). 517–525. 1 indexed citations
5.
Miryala, Sravan Kumar, Soumya Basu, Aniket Naha, et al.. (2021). Identification of bioactive natural compounds as efficient inhibitors against Mycobacterium tuberculosis protein-targets: A molecular docking and molecular dynamics simulation study. Journal of Molecular Liquids. 341. 117340–117340. 45 indexed citations
6.
Padmapriyadarsini, Chandrasekaran, Saravanan Natarajan, Ramalingam Bethunaickan, & Srikanth Tripathy. (2017). Malnutrition: Modulator of Immune Responses in Tuberculosis. Frontiers in Immunology. 8. 1316–1316. 84 indexed citations
7.
Ibrahim, Ahamed, Saravanan Natarajan, & Ghafoorunissa. (2005). Dietary trans–fatty acids alter adipocyte plasma membrane fatty acid composition and insulin sensitivity in rats. Metabolism. 54(2). 240–246. 91 indexed citations
8.
Natarajan, Saravanan, et al.. (2005). Differential effects of dietary saturated and trans-fatty acids on expression of genes associated with insulin sensitivity in rat adipose tissue. European Journal of Endocrinology. 153(1). 159–165. 110 indexed citations
9.
Ghafoorunissa, Ahamed Ibrahim, & Saravanan Natarajan. (2004). Substituting dietary linoleic acid with α-linolenic acid improves insulin sensitivity in sucrose fed rats. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1733(1). 67–75. 61 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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2026