Deepa Shukla

1.6k total citations
22 papers, 1.2k citations indexed

About

Deepa Shukla is a scholar working on Cancer Research, Molecular Biology and Genetics. According to data from OpenAlex, Deepa Shukla has authored 22 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cancer Research, 11 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in Deepa Shukla's work include Cancer, Hypoxia, and Metabolism (13 papers), Epigenetics and DNA Methylation (3 papers) and Medicinal Plants and Neuroprotection (2 papers). Deepa Shukla is often cited by papers focused on Cancer, Hypoxia, and Metabolism (13 papers), Epigenetics and DNA Methylation (3 papers) and Medicinal Plants and Neuroprotection (2 papers). Deepa Shukla collaborates with scholars based in United Kingdom, United States and India. Deepa Shukla's co-authors include Patrick H. Maxwell, Maxine Tran, Sarah K. Harten, Peter Carmeliet, Julián Aragonés, Peter Hill, H. Terence Cook, Miguel A. Esteban, Margaret Ashcroft and Thomas Briston and has published in prestigious journals such as Journal of Clinical Investigation, PLoS ONE and Cancer Cell.

In The Last Decade

Deepa Shukla

20 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deepa Shukla United Kingdom 15 667 557 207 196 172 22 1.2k
Gengyin Zhou China 26 1.0k 1.5× 366 0.7× 179 0.9× 136 0.7× 223 1.3× 61 1.8k
Frédérique Savagner France 24 1.0k 1.5× 279 0.5× 120 0.6× 298 1.5× 183 1.1× 58 2.2k
Valentina Câmpean Germany 19 521 0.8× 234 0.4× 218 1.1× 189 1.0× 165 1.0× 30 1.3k
Kshama Mehta United States 19 925 1.4× 532 1.0× 213 1.0× 139 0.7× 379 2.2× 22 1.8k
Xiangchen Gu China 11 678 1.0× 341 0.6× 94 0.5× 205 1.0× 81 0.5× 24 1.1k
Jason Gay United States 18 653 1.0× 309 0.6× 120 0.6× 201 1.0× 203 1.2× 30 1.6k
Geneviève Robitaille Canada 14 528 0.8× 360 0.6× 140 0.7× 128 0.7× 66 0.4× 17 1.1k
Silvia Liu United States 21 796 1.2× 255 0.5× 154 0.7× 154 0.8× 244 1.4× 95 1.6k
Sawako Suzuki Japan 21 684 1.0× 531 1.0× 202 1.0× 68 0.3× 458 2.7× 58 1.7k
Shiying Cui Canada 17 1.2k 1.8× 361 0.6× 223 1.1× 318 1.6× 240 1.4× 24 1.8k

Countries citing papers authored by Deepa Shukla

Since Specialization
Citations

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

Fields of papers citing papers by Deepa Shukla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepa Shukla

This figure shows the co-authorship network connecting the top 25 collaborators of Deepa Shukla. A scholar is included among the top collaborators of Deepa Shukla 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 Deepa Shukla. Deepa Shukla 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.
Shukla, Deepa, Khatuna Gabunia, Shannon E. McGettigan, et al.. (2025). CAR Binders Affect CAR T-cell Tonic Signaling, Durability, and Sensitivity to Target. Cancer Immunology Research. 13(6). 867–880. 1 indexed citations
2.
3.
Shukla, Deepa, Sasikanth Manne, Shuguang Jiang, et al.. (2025). Optimal pairing of binder and co-stimulatory domains improves dual CART cell efficacy. Molecular Therapy. 33(11). 5556–5571.
4.
5.
Tran, Maxine, B. Bibby, Lingjian Yang, et al.. (2020). Independence of HIF1a and androgen signaling pathways in prostate cancer. BMC Cancer. 20(1). 469–469. 28 indexed citations
6.
Chauhan, Prashant, Deepa Shukla, Debprasad Chattopadhyay, & Bhaskar Saha. (2017). Redundant and regulatory roles for Toll-like receptors inLeishmaniainfection. Clinical & Experimental Immunology. 190(2). 167–186. 36 indexed citations
7.
Ong, Sang-Ging, Won Hee Lee, Kazuki Kodo, et al.. (2014). HIF-1 reduces ischaemia–reperfusion injury in the heart by targeting the mitochondrial permeability transition pore. Cardiovascular Research. 104(1). 24–36. 137 indexed citations
8.
Sun, Lijun, Wen‐de Tian, Deepa Shukla, et al.. (2012). Epigenetic regulation of HIF-1 alpha in renal cancer cells involves HIF-1 alpha/2 alpha binding to a reverse hypoxia-response element. UCL Discovery (University College London). 2 indexed citations
9.
Schietke, Ruth, Thomas Hackenbeck, Maxine Tran, et al.. (2012). Renal Tubular HIF-2α Expression Requires VHL Inactivation and Causes Fibrosis and Cysts. PLoS ONE. 7(1). e31034–e31034. 69 indexed citations
10.
Yang, Jun, Oliver Staples, Luke W. Thomas, et al.. (2012). Human CHCHD4 mitochondrial proteins regulate cellular oxygen consumption rate and metabolism and provide a critical role in hypoxia signaling and tumor progression. Journal of Clinical Investigation. 122(2). 600–611. 77 indexed citations
11.
Xu, Jianyong, Yan Xu, Li Sun, et al.. (2011). Epigenetic regulation of HIF-1α in renal cancer cells involves HIF-1α/2α binding to a reverse hypoxia-response element. Oncogene. 31(8). 1065–1072. 30 indexed citations
12.
Schley, Gunnar, Bernd Klanke, Johannes Schödel, et al.. (2011). Hypoxia-Inducible Transcription Factors Stabilization in the Thick Ascending Limb Protects against Ischemic Acute Kidney Injury. Journal of the American Society of Nephrology. 22(11). 2004–2015. 83 indexed citations
13.
Harten, Sarah K., Miguel A. Esteban, Deepa Shukla, Margaret Ashcroft, & Patrick H. Maxwell. (2011). Inactivation of the von Hippel-Lindau tumour suppressor gene induces Neuromedin U expression in renal cancer cells. Molecular Cancer. 10(1). 89–89. 30 indexed citations
14.
Mowat, Freya M., Ulrich F. O. Luhmann, Alexander J. Smith, et al.. (2010). HIF-1alpha and HIF-2alpha Are Differentially Activated in Distinct Cell Populations in Retinal Ischaemia. PLoS ONE. 5(6). e11103–e11103. 90 indexed citations
15.
Xu, Jianyong, Huapeng Li, Bo Wang, et al.. (2010). VHL Inactivation Induces HEF1 and Aurora Kinase A. Journal of the American Society of Nephrology. 21(12). 2041–2046. 57 indexed citations
16.
17.
Cantley, James, Colin Selman, Deepa Shukla, et al.. (2008). Deletion of the von Hippel–Lindau gene in pancreatic β cells impairs glucose homeostasis in mice. Journal of Clinical Investigation. 119(1). 125–35. 102 indexed citations
18.
Hill, Peter, Deepa Shukla, Maxine Tran, et al.. (2008). Inhibition of Hypoxia Inducible Factor Hydroxylases Protects Against Renal Ischemia-Reperfusion Injury. Journal of the American Society of Nephrology. 19(1). 39–46. 230 indexed citations
19.
Harten, Sarah K., Deepa Shukla, Ravi Barod, et al.. (2008). Regulation of Renal Epithelial Tight Junctions by the von Hippel-Lindau Tumor Suppressor Gene Involves Occludin and Claudin 1 and Is Independent of E-Cadherin. Molecular Biology of the Cell. 20(3). 1089–1101. 67 indexed citations
20.
Pollard, Patrick J., Bradley Spencer‐Dene, Deepa Shukla, et al.. (2007). Targeted Inactivation of Fh1 Causes Proliferative Renal Cyst Development and Activation of the Hypoxia Pathway. Cancer Cell. 11(4). 311–319. 129 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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