Deepthi Ashok

922 total citations
18 papers, 648 citations indexed

About

Deepthi Ashok is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Biophysics. According to data from OpenAlex, Deepthi Ashok has authored 18 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Pathology and Forensic Medicine and 3 papers in Biophysics. Recurrent topics in Deepthi Ashok's work include Mitochondrial Function and Pathology (11 papers), Cardiac Ischemia and Reperfusion (5 papers) and ATP Synthase and ATPases Research (4 papers). Deepthi Ashok is often cited by papers focused on Mitochondrial Function and Pathology (11 papers), Cardiac Ischemia and Reperfusion (5 papers) and ATP Synthase and ATPases Research (4 papers). Deepthi Ashok collaborates with scholars based in United States, United Kingdom and Italy. Deepthi Ashok's co-authors include Martin D. Brand, Anne N. Murphy, Álvaro A. Elorza, George W. Rogers, Susanna Petrosyan, David A. Ferrick, Brian O’Rourke, Robert E. Hughes, Tong Shi and Adam L. Orr and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and PLoS ONE.

In The Last Decade

Deepthi Ashok

16 papers receiving 645 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deepthi Ashok United States 11 458 187 68 65 55 18 648
Blake R. Zelickson United States 7 479 1.0× 169 0.9× 63 0.9× 82 1.3× 76 1.4× 8 765
Daniela P. Converso Argentina 12 475 1.0× 221 1.2× 62 0.9× 38 0.6× 29 0.5× 15 716
Wichit Suthammarak United States 9 534 1.2× 122 0.7× 44 0.6× 62 1.0× 93 1.7× 13 734
Liesbeth T. Wintjes Netherlands 12 588 1.3× 127 0.7× 116 1.7× 63 1.0× 173 3.1× 19 847
Saori Morota Sweden 14 463 1.0× 154 0.8× 73 1.1× 32 0.5× 95 1.7× 19 783
Muhammad Rizwan Alam Pakistan 13 669 1.5× 171 0.9× 105 1.5× 58 0.9× 56 1.0× 28 922
Michael Trenker Austria 9 571 1.2× 251 1.3× 34 0.5× 47 0.7× 44 0.8× 10 715
Yulia Baburina Russia 15 464 1.0× 116 0.6× 85 1.3× 39 0.6× 31 0.6× 52 658
Leonardo Y. Tanaka Brazil 14 373 0.8× 227 1.2× 47 0.7× 72 1.1× 34 0.6× 18 863
Agnieszka Kozieł Poland 12 423 0.9× 180 1.0× 115 1.7× 45 0.7× 17 0.3× 14 657

Countries citing papers authored by Deepthi Ashok

Since Specialization
Citations

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

Fields of papers citing papers by Deepthi Ashok

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepthi Ashok

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

All Works

18 of 18 papers shown
1.
Papanicolaou, Kyriakos N., Wenxi Zhang, Aidan Dunphy, et al.. (2025). Loss of O-GlcNAcylation in cardiac myocytes triggers the integrated stress response, contributing to heart failure. Journal of Biological Chemistry. 301(12). 110818–110818.
2.
3.
Papanicolaou, Kyriakos N., Deepthi Ashok, Wenxi Zhang, et al.. (2023). Inhibiting O-GlcNAcylation impacts p38 and Erk1/2 signaling and perturbs cardiomyocyte hypertrophy. Journal of Biological Chemistry. 299(3). 102907–102907. 15 indexed citations
4.
Ashok, Deepthi, Kyriakos N. Papanicolaou, Agnieszka Sidor, et al.. (2023). Mitochondrial membrane potential instability on reperfusion after ischemia does not depend on mitochondrial Ca2+ uptake. Journal of Biological Chemistry. 299(6). 104708–104708. 17 indexed citations
5.
Ashok, Deepthi & Brian O’Rourke. (2021). MitoWave: Spatiotemporal analysis of mitochondrial membrane potential fluctuations during I/R. Biophysical Journal. 120(16). 3261–3271. 7 indexed citations
6.
Mishra, Sumita, Nandhini Sadagopan, Brittany Dunkerly‐Eyring, et al.. (2021). Inhibition of phosphodiesterase type 9 reduces obesity and cardiometabolic syndrome in mice. Journal of Clinical Investigation. 131(21). 23 indexed citations
7.
Ashok, Deepthi, Mark J. Kohr, Roopa Biswas, et al.. (2020). Nuclear-mitochondrial communication involving miR-181c plays an important role in cardiac dysfunction during obesity. Journal of Molecular and Cellular Cardiology. 144. 87–96. 21 indexed citations
8.
O’Rourke, Brian, Deepthi Ashok, & Ting Liu. (2020). Mitochondrial Ca2+ in heart failure: Not enough or too much?. Journal of Molecular and Cellular Cardiology. 151. 126–134. 34 indexed citations
9.
Ashok, Deepthi, Kyriakos N. Papanicolaou, Ting Liu, & Brian O’Rourke. (2020). Reverse-Mode Mitochondrial Na+/Ca2+ Exchange, Not the MCU, is the Primary Mode of Ca2+ Import into the Mitochondria during Ischemia/Reperfusion in Neonatal Cardiac Myocytes. Biophysical Journal. 118(3). 407a–407a. 1 indexed citations
10.
Papanicolaou, Kyriakos N., Deepthi Ashok, Ting Liu, et al.. (2020). Global knockout of ROMK potassium channel worsens cardiac ischemia-reperfusion injury but cardiomyocyte-specific knockout does not: Implications for the identity of mitoKATP. Journal of Molecular and Cellular Cardiology. 139. 176–189. 28 indexed citations
11.
Ashok, Deepthi, et al.. (2020). A Rare Case of Lipomyelocele. 3(10). 378–380. 1 indexed citations
12.
Ashok, Deepthi, Kyriakos N. Papanicolaou, Ting Liu, & Brian O’Rourke. (2020). Abstract 554: Reverse-mode Mitochondrial Na + / Ca2+ Mitochondrial Exchange, Not the Mcu, is the Primary Mode of Ca2+ Import Into the Mitochondria During Ischemia/ Reperfusion in Neonatal Cardiac Myocytes. Circulation Research. 127(Suppl_1). 1 indexed citations
13.
Ashok, Deepthi, et al.. (2018). Enhancing Mitochondrial Biogenesis with a CRISPR/ndCas9 Adenoviral Vector System in Cardiomyocytes. Biophysical Journal. 114(3). 662a–662a. 1 indexed citations
14.
Wiley, Laura, Deepthi Ashok, Carmen Martín-Ruiz, et al.. (2014). Reactive Oxygen Species Production and Mitochondrial Dysfunction in White Blood Cells Are Not Valid Biomarkers of Ageing in the Very Old. PLoS ONE. 9(3). e91005–e91005. 10 indexed citations
15.
Orr, Adam L., Deepthi Ashok, Melissa R. Sarantos, et al.. (2014). Novel Inhibitors of Mitochondrial sn-Glycerol 3-phosphate Dehydrogenase. PLoS ONE. 9(2). e89938–e89938. 49 indexed citations
16.
Orr, Adam L., Deepthi Ashok, Melissa R. Sarantos, et al.. (2013). Inhibitors of ROS production by the ubiquinone-binding site of mitochondrial complex I identified by chemical screening. Free Radical Biology and Medicine. 65. 1047–1059. 69 indexed citations
17.
Collerton, Joanna, Deepthi Ashok, Carmen Martín-Ruiz, et al.. (2013). Frailty and mortality are not influenced by mitochondrial DNA haplotypes in the very old. Neurobiology of Aging. 34(12). 2889.e1–2889.e4. 14 indexed citations
18.
Rogers, George W., Martin D. Brand, Susanna Petrosyan, et al.. (2011). High Throughput Microplate Respiratory Measurements Using Minimal Quantities Of Isolated Mitochondria. PLoS ONE. 6(7). e21746–e21746. 357 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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