Ritwik Datta

874 total citations
17 papers, 448 citations indexed

About

Ritwik Datta is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Immunology. According to data from OpenAlex, Ritwik Datta has authored 17 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Cardiology and Cardiovascular Medicine and 5 papers in Immunology. Recurrent topics in Ritwik Datta's work include Cardiac Fibrosis and Remodeling (5 papers), Signaling Pathways in Disease (4 papers) and Heat shock proteins research (3 papers). Ritwik Datta is often cited by papers focused on Cardiac Fibrosis and Remodeling (5 papers), Signaling Pathways in Disease (4 papers) and Heat shock proteins research (3 papers). Ritwik Datta collaborates with scholars based in India, United States and Japan. Ritwik Datta's co-authors include Sagartirtha Sarkar, Michael J. Podolsky, Kamran Atabai, Santanu Rana, Arkadeep Mitra, Kaberi Datta, Mamta Chawla‐Sarkar, Shantanu Sengupta, Durba Banerjee and Carlos O. Lizama and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Ritwik Datta

17 papers receiving 444 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ritwik Datta India	11	235	161	91	78	47	17	448
Bengt Kull Sweden	8	231 1.0×	81 0.5×	139 1.5×	59 0.8×	41 0.9×	12	453
Jin-Ho Kang South Korea	14	258 1.1×	90 0.6×	53 0.6×	112 1.4×	60 1.3×	26	629
Hexiang Cheng China	7	269 1.1×	117 0.7×	142 1.6×	69 0.9×	37 0.8×	15	480
Е. Л. Лушникова Russia	10	157 0.7×	103 0.6×	45 0.5×	50 0.6×	54 1.1×	140	475
Antoinette Bugyei‐Twum Canada	9	195 0.8×	158 1.0×	36 0.4×	53 0.7×	69 1.5×	11	416
Jong‐Wei Lin Taiwan	10	275 1.2×	110 0.7×	92 1.0×	105 1.3×	151 3.2×	15	541
Boquan Wu China	13	357 1.5×	60 0.4×	50 0.5×	79 1.0×	29 0.6×	23	548
Zena Huang China	12	360 1.5×	64 0.4×	49 0.5×	46 0.6×	60 1.3×	26	621
Carolin Zwadlo Germany	11	205 0.9×	225 1.4×	41 0.5×	59 0.8×	102 2.2×	25	508
Emily C. Britt United States	7	304 1.3×	183 1.1×	50 0.5×	68 0.9×	56 1.2×	10	652

Countries citing papers authored by Ritwik Datta

Since Specialization

Citations

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

Fields of papers citing papers by Ritwik Datta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ritwik Datta

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

All Works

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17 of 17 papers shown

Podolsky, Michael J., Carlos O. Lizama, Ritwik Datta, et al.. (2024). Genome-wide screens identify SEL1L as an intracellular rheostat controlling collagen turnover. Nature Communications. 15(1). 1531–1531. 5 indexed citations

Datta, Ritwik, Michael J. Podolsky, Diana Alba, et al.. (2024). PTP1B mediates the inhibitory effect of MFGE8 on insulin signaling through the β5 integrin. Journal of Biological Chemistry. 300(2). 105631–105631. 3 indexed citations

Datta, Ritwik, Regan Volk, Sinan Lin, et al.. (2023). MFGE8 links absorption of dietary fatty acids with catabolism of enterocyte lipid stores through HNF4γ-dependent transcription of CES enzymes. Cell Reports. 42(3). 112249–112249. 3 indexed citations

Datta, Ritwik, et al.. (2022). Cardiomyocyte-specific regression of nitrosative stress-mediated S-Nitrosylation of IKKγ alleviates pathological cardiac hypertrophy. Cellular Signalling. 98. 110403–110403. 3 indexed citations

Datta, Ritwik, Carlos O. Lizama, William McKleroy, et al.. (2021). Autoregulation of insulin receptor signaling through MFGE8 and the αvβ5 integrin. Proceedings of the National Academy of Sciences. 118(18). 9 indexed citations

Podolsky, Michael J., Carlos O. Lizama, Ritwik Datta, et al.. (2020). Age-dependent regulation of cell-mediated collagen turnover. JCI Insight. 5(10). 39 indexed citations

Rana, Santanu, et al.. (2018). Nanotized PPARα Overexpression Targeted to Hypertrophied Myocardium Improves Cardiac Function by Attenuating the p53-GSK3β-Mediated Mitochondrial Death Pathway. Antioxidants and Redox Signaling. 30(5). 713–732. 20 indexed citations

Khalifeh‐Soltani, Amin, et al.. (2018). The Mfge8‐α8β1;1‐PTEN pathway regulates airway smooth muscle contraction in allergic inflammation. The FASEB Journal. 32(11). 5927–5936. 20 indexed citations

Datta, Ritwik, Michael J. Podolsky, & Kamran Atabai. (2018). Fat fibrosis: friend or foe?. JCI Insight. 3(19). 93 indexed citations

10.

Podolsky, Michael J., Amin Khalifeh‐Soltani, William McKleroy, et al.. (2018). Cell division cycle 7 kinase is a negative regulator of cell-mediated collagen degradation. American Journal of Physiology-Lung Cellular and Molecular Physiology. 315(3). L360–L370. 3 indexed citations

11.

Mitra, Arkadeep, Ritwik Datta, Santanu Rana, & Sagartirtha Sarkar. (2017). Modulation of NFKB1/p50 by ROS leads to impaired ATP production during MI compared to cardiac hypertrophy. Journal of Cellular Biochemistry. 119(2). 1575–1590. 14 indexed citations

12.

Datta, Ritwik, et al.. (2016). Myocyte-Derived Hsp90 Modulates Collagen Upregulation via Biphasic Activation of STAT-3 in Fibroblasts during Cardiac Hypertrophy. Molecular and Cellular Biology. 37(6). 87 indexed citations

13.

Rana, Santanu, et al.. (2015). Improved bioavailability of targeted Curcumin delivery efficiently regressed cardiac hypertrophy by modulating apoptotic load within cardiac microenvironment. Toxicology and Applied Pharmacology. 290. 54–65. 44 indexed citations

14.

Datta, Ritwik, Santanu Rana, Kaberi Datta, et al.. (2015). Hsp90/Cdc37 assembly modulates TGFβ receptor-II to act as a profibrotic regulator of TGFβ signaling during cardiac hypertrophy. Cellular Signalling. 27(12). 2410–2424. 28 indexed citations

15.

Datta, Kaberi, et al.. (2014). Differential and Conditional Activation of PKC-Isoforms Dictates Cardiac Adaptation during Physiological to Pathological Hypertrophy. PLoS ONE. 9(8). e104711–e104711. 15 indexed citations

16.

Mitra, Arkadeep, Trayambak Basak, Shadab Ahmad, et al.. (2014). Comparative Proteome Profiling during Cardiac Hypertrophy and Myocardial Infarction Reveals Altered Glucose Oxidation by Differential Activation of Pyruvate Dehydrogenase E1 Component Subunit β. Journal of Molecular Biology. 427(11). 2104–2120. 22 indexed citations

17.

Mitra, Arkadeep, et al.. (2014). Cardioprotective Role of P38 MAPK During Myocardial Infarction Via Parallel Activation of α‐Crystallin B and Nrf2. Journal of Cellular Physiology. 229(9). 1272–1282. 40 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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