Sunil Sudarshan

2.9k total citations
61 papers, 1.8k citations indexed

About

Sunil Sudarshan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Sunil Sudarshan has authored 61 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 25 papers in Pulmonary and Respiratory Medicine and 24 papers in Cancer Research. Recurrent topics in Sunil Sudarshan's work include Renal cell carcinoma treatment (23 papers), Cancer, Hypoxia, and Metabolism (18 papers) and Renal and related cancers (15 papers). Sunil Sudarshan is often cited by papers focused on Renal cell carcinoma treatment (23 papers), Cancer, Hypoxia, and Metabolism (18 papers) and Renal and related cancers (15 papers). Sunil Sudarshan collaborates with scholars based in United States, India and Finland. Sunil Sudarshan's co-authors include W. Marston Linehan, Len Neckers, Gennady Bratslavsky, Karen Block, Peter A. Pinto, Karthigayan Shanmugasundaram, Ralph J. DeBerardinis, Navdeep S. Chandel, Andrew R. Mullen and Hien P. Nguyen and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Sunil Sudarshan

55 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sunil Sudarshan United States 26 1.3k 644 630 205 170 61 1.8k
Qiaoyou Weng China 26 1.3k 1.0× 640 1.0× 619 1.0× 293 1.4× 96 0.6× 77 2.2k
Chung‐Ping Hsu Taiwan 23 877 0.7× 292 0.5× 415 0.7× 269 1.3× 237 1.4× 67 1.6k
Zhaodong Han China 26 1.2k 0.9× 704 1.1× 414 0.7× 403 2.0× 150 0.9× 76 1.8k
Kenji Schorpp Germany 18 969 0.8× 458 0.7× 562 0.9× 174 0.8× 108 0.6× 42 1.5k
Steven L. Wood United Kingdom 23 970 0.8× 334 0.5× 332 0.5× 431 2.1× 139 0.8× 35 1.8k
Francis Vacherot France 29 1.1k 0.9× 454 0.7× 1.2k 1.9× 349 1.7× 138 0.8× 73 2.5k
Yahya Elshimali United States 20 703 0.5× 498 0.8× 348 0.6× 494 2.4× 74 0.4× 36 1.4k
Litong Nie United States 16 1.2k 1.0× 634 1.0× 812 1.3× 320 1.6× 84 0.5× 31 1.9k
Zhi‐Guang Huang China 19 1.5k 1.2× 1.1k 1.7× 246 0.4× 246 1.2× 180 1.1× 110 2.3k

Countries citing papers authored by Sunil Sudarshan

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Sudarshan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunil Sudarshan

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Sudarshan. A scholar is included among the top collaborators of Sunil Sudarshan 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 Sunil Sudarshan. Sunil Sudarshan 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.
Bansal, Mohit, et al.. (2025). DKC1-mediated pseudouridylation of rRNA targets hnRNP A1 to sustain IRES-dependent translation and ATF4-driven metabolic adaptation. Science Advances. 11(35). eadv9401–eadv9401. 2 indexed citations
2.
Nam, Hyeyoung, Anirban Kundu, Suman Karki, et al.. (2025). HDAC7 promotes renal cancer progression by reprogramming branched-chain amino acid metabolism. Science Advances. 11(23). eadt3552–eadt3552.
3.
Tourigny, Jason P., Katherine Beebe, Hongde Li, et al.. (2024). Renal L-2-hydroxyglutarate dehydrogenase activity promotes hypoxia tolerance and mitochondrial metabolism in Drosophila melanogaster. Molecular Metabolism. 89. 102013–102013. 1 indexed citations
4.
Tran, Gia‐Buu, Bingwei Ye, Yajie Yu, et al.. (2023). Caffeine Supplementation and FOXM1 Inhibition Enhance the Antitumor Effect of Statins in Neuroblastoma. Cancer Research. 83(13). 2248–2261. 8 indexed citations
5.
McMeekin, Laura J., Cody Savage, Micah Simmons, et al.. (2022). Estrogen-related receptor gamma regulates mitochondrial and synaptic genes and modulates vulnerability to synucleinopathy. npj Parkinson s Disease. 8(1). 106–106. 19 indexed citations
6.
Nam, Hyeyoung, Anirban Kundu, Suman Karki, et al.. (2021). The TGF-β/HDAC7 axis suppresses TCA cycle metabolism in renal cancer. JCI Insight. 6(22). 23 indexed citations
7.
Brinkley, Garrett J., Hongde Li, Jonathan A. Karty, et al.. (2020). The oncometabolite L-2-hydroxyglutarate is a common product of dipteran larval development. Insect Biochemistry and Molecular Biology. 127. 103493–103493. 6 indexed citations
8.
Kundu, Anirban, Hyeyoung Nam, Sandeep B. Shelar, et al.. (2020). PRDM16 suppresses HIF-targeted gene expression in kidney cancer. The Journal of Experimental Medicine. 217(6). 29 indexed citations
9.
Nam, Hyeyoung, Anirban Kundu, Garrett J. Brinkley, et al.. (2020). PGC1α suppresses kidney cancer progression by inhibiting collagen-induced SNAIL expression. Matrix Biology. 89. 43–58. 20 indexed citations
10.
11.
Nam, Hyeyoung, Darshan S. Chandrashekar, Anirban Kundu, et al.. (2018). Integrative Epigenetic and Gene Expression Analysis of Renal Tumor Progression to Metastasis. Molecular Cancer Research. 17(1). 84–96. 34 indexed citations
12.
Shanmugasundaram, Karthigayan, B. K. Nayak, Eun‐Hee Shim, et al.. (2014). The Oncometabolite Fumarate Promotes Pseudohypoxia Through Noncanonical Activation of NF-κB Signaling. Journal of Biological Chemistry. 289(35). 24691–24699. 48 indexed citations
13.
Sudarshan, Sunil, et al.. (2013). PREVALENCE OF FOOD BORNE PATHOGENS IN MARKET SAMPLES OF CHICKEN MEAT IN BANGALORE, INDIA. Indian Journal of Animal Research. 47(3). 262–264. 6 indexed citations
14.
Sullivan, Lucas B., Eva Martínez-García, Hien Nguyen, et al.. (2013). The Proto-oncometabolite Fumarate Binds Glutathione to Amplify ROS-Dependent Signaling. Molecular Cell. 51(2). 273–273. 6 indexed citations
15.
Sudarshan, Sunil, José A. Karam, James Brugarolas, et al.. (2012). Metabolism of Kidney Cancer: From the Lab to Clinical Practice. European Urology. 63(2). 244–251. 61 indexed citations
16.
Shanmugasundaram, Karthigayan, Karen Block, B. K. Nayak, et al.. (2012). PI3K regulation of the SKP-2/p27 axis through mTORC2. Oncogene. 32(16). 2027–2036. 38 indexed citations
17.
Sudarshan, Sunil, et al.. (2011). A study on prescription pattern of Antihypertensives. Indian Journal of Pharmacy Practice. 4(1). 1 indexed citations
18.
Sudarshan, Sunil, Karthigayan Shanmugasundaram, Susan L. Naylor, et al.. (2011). Reduced Expression of Fumarate Hydratase in Clear Cell Renal Cancer Mediates HIF-2α Accumulation and Promotes Migration and Invasion. PLoS ONE. 6(6). e21037–e21037. 44 indexed citations
19.
Sourbier, Carole, Alessio Giubellino, Youfeng Yang, et al.. (2010). Increasing reactive oxygen species as a therapeutic approach to treat hereditary leiomyomatosis and renal cell carcinoma. Cell Cycle. 9(20). 4183–4189. 25 indexed citations
20.
Sudarshan, Sunil, et al.. (2009). Possible Role of Natural Nephroprotective; Hemidesmus indicus in Congestive Heart Failure. Pharmacognosy Research. 1(6). 367. 4 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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