Rakesh Dixit

3.7k total citations
137 papers, 2.6k citations indexed

About

Rakesh Dixit is a scholar working on Molecular Biology, Pharmacology and Food Science. According to data from OpenAlex, Rakesh Dixit has authored 137 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 23 papers in Pharmacology and 16 papers in Food Science. Recurrent topics in Rakesh Dixit's work include Pharmacogenetics and Drug Metabolism (13 papers), Natural Antidiabetic Agents Studies (10 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). Rakesh Dixit is often cited by papers focused on Pharmacogenetics and Drug Metabolism (13 papers), Natural Antidiabetic Agents Studies (10 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). Rakesh Dixit collaborates with scholars based in India, United States and France. Rakesh Dixit's co-authors include Hasan Mukhtar, David R. Bickers, Prahlad K. Seth, Mary Jane Hinrichs, Barry Gold, Mukul Das, Steven Coats, Urs A. Boelsterli, Gary D. Stoner and Kevin P. Keenan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Rakesh Dixit

128 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rakesh Dixit India 28 778 636 476 281 259 137 2.6k
Hua Zhou China 30 1.2k 1.5× 313 0.5× 257 0.5× 164 0.6× 155 0.6× 184 2.9k
Hideki Mori Japan 36 1.7k 2.2× 424 0.7× 275 0.6× 521 1.9× 234 0.9× 190 4.3k
Shigeru Murakami Japan 36 1.1k 1.5× 665 1.0× 276 0.6× 354 1.3× 178 0.7× 147 3.7k
Federica Rizzi Italy 26 892 1.1× 521 0.8× 247 0.5× 287 1.0× 194 0.7× 47 2.5k
Jie Shi China 25 937 1.2× 455 0.7× 164 0.3× 518 1.8× 290 1.1× 146 3.6k
Ping Zhao China 28 1.5k 1.9× 465 0.7× 136 0.3× 220 0.8× 309 1.2× 147 2.9k
George Notas Greece 31 1.1k 1.4× 534 0.8× 86 0.2× 280 1.0× 230 0.9× 106 3.4k
Maria Russo Italy 30 1.7k 2.2× 365 0.6× 109 0.2× 361 1.3× 242 0.9× 76 3.7k
Huachen Wei United States 33 1.2k 1.6× 257 0.4× 104 0.2× 376 1.3× 166 0.6× 79 3.6k
Mamoru Isemura Japan 37 1.5k 2.0× 376 0.6× 128 0.3× 346 1.2× 95 0.4× 123 4.1k

Countries citing papers authored by Rakesh Dixit

Since Specialization
Citations

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

Fields of papers citing papers by Rakesh Dixit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rakesh Dixit

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

All Works

20 of 20 papers shown
1.
Sharma, Anurag, et al.. (2025). The impact of pharmacological agents on neuroinflammation in neurodegenerative diseases. SHILAP Revista de lepidopterología. 71(2). 95–105.
2.
3.
Dixit, Rakesh, et al.. (2024). Artificial Intelligence Meets AY (Ayurveda): Bridging Tradition, Technology, and Super technology for Diabetes Care. Journal of Ayurvedic and Herbal Medicine. 10(4). 113–114.
4.
5.
Pore, Nabendu, Kevin Schifferli, Noel R. Monks, et al.. (2018). Discovery and Development of MEDI7247, a Novel Pyrrolobenzodiazepine (PBD)-Based Antibody Drug Conjugate Targeting ASCT2, for Treating Hematological Cancers. Blood. 132(Supplement 1). 4071–4071. 7 indexed citations
6.
Srivastava, Saurabh, Shadab Mohammad, Shalini Gupta, et al.. (2018). Chemoprotective effect of nanocurcumin on 5-fluorouracil-induced-toxicity toward oral cancer treatment. National Journal of Maxillofacial Surgery. 9(2). 160–160. 21 indexed citations
7.
Nath, Rajendra, et al.. (2017). An experimental study to see the antihypertensive effects of gymnema sylvestre and acorus calamus in wistar rats and its comparison with amlodipine. SHILAP Revista de lepidopterología. 8(3). 11–15. 2 indexed citations
8.
Kumar, Devendra, et al.. (2016). Evaluation of the potential effect of Allium sativum, Momordica charantia, Eugenia jambolana, Ocimum sanctum and Psidium guajava on intestinal P-glycoprotein in rats. Journal of Intercultural Ethnopharmacology. 6(1). 68–68. 6 indexed citations
9.
Ansari, Valeed Ahmad, Muhammad Arif, Md. Sarfaraj Hussain, Hefazat Hussain Siddiqui, & Rakesh Dixit. (2016). New 4′-substituted benzoyl-β-D glycoside from the fruit pulp of Terminalia belerica with antiplatelet and antioxidant potency. Integrative Medicine Research. 5(4). 317–323. 6 indexed citations
10.
Dixit, Rakesh, et al.. (2014). Drug Screening Methods (Preclinical Evaluation of New drugs). 8(1). 126–127. 9 indexed citations
11.
Dixit, Rakesh, et al.. (2013). CLINICAL EVALUATION OF ANTI-HYPERGLYCEMIC ACTIVITY OF OCIMUM SANCTUM IN COMPARISON WITH GLIBENCLAMIDE IN THE RAT MODEL OF T2DM. International Journal of Pharma and Bio Sciences. 2 indexed citations
12.
Dixit, Rakesh, et al.. (2013). ROLE OF SELECTIVE ESTROGEN RECEPTOR MODULATORS (SERM) IN TREATMENT OF CARCINOMA PROSTATE.. International Journal of Pharma and Bio Sciences.
13.
Rathi, Himani, et al.. (2013). An Experimental Study to Evaluate the Antihyperglycemic Action of Curcumin in Diabetes Rat Model and Comparison with Glibenclamide. International Journal of Health Sciences and Research. 3(3). 37–43. 1 indexed citations
14.
Dixit, Rakesh, et al.. (2012). Essentials of Medical Pharmacology. 6(1). 104–106. 1 indexed citations
15.
Dixit, Rakesh, et al.. (2012). Basic Principles of Clinical Research and Methodology. 6(2). 1 indexed citations
16.
Dixit, Rakesh, Laurie Iciek, Kathleen McKeever, & Patricia C. Ryan. (2009). Challenges of general safety evaluations of biologics compared to small molecule pharmaceuticals in animal models. Expert Opinion on Drug Discovery. 5(1). 79–94. 9 indexed citations
17.
Valerio, Luis G. & Rakesh Dixit. (2008). Computational Toxicology. Toxicology Mechanisms and Methods. 18(2-3). 97–99. 3 indexed citations
18.
Dixit, Rakesh & Urs A. Boelsterli. (2007). Healthy animals and animal models of human disease(s) in safety assessment of human pharmaceuticals, including therapeutic antibodies. Drug Discovery Today. 12(7-8). 336–342. 83 indexed citations
19.
Stoner, Gary D., Haiyan Qin, Tong Chen, et al.. (2005). The effects of L-748706, a selective cyclooxygenase-2 inhibitor, on N -nitrosomethylbenzylamine-induced rat esophageal tumorigenesis. Carcinogenesis. 26(9). 1590–1595. 21 indexed citations
20.
Panigrahi, Aswini K., Subrat Kumar Panda, Rakesh Dixit, et al.. (1997). Magnitude of hepatitis C virus infection in India: prevalence in healthy blood donors, acute and chronic liver diseases.. PubMed. 51(3). 167–74. 63 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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