Arijit Chakravarty

1.8k total citations
50 papers, 1.2k citations indexed

About

Arijit Chakravarty is a scholar working on Molecular Biology, Cell Biology and Infectious Diseases. According to data from OpenAlex, Arijit Chakravarty has authored 50 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 16 papers in Cell Biology and 12 papers in Infectious Diseases. Recurrent topics in Arijit Chakravarty's work include Microtubule and mitosis dynamics (16 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and COVID-19 epidemiological studies (10 papers). Arijit Chakravarty is often cited by papers focused on Microtubule and mitosis dynamics (16 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and COVID-19 epidemiological studies (10 papers). Arijit Chakravarty collaborates with scholars based in United States, Japan and India. Arijit Chakravarty's co-authors include Jeffrey Ecsedy, Jonathan M. Carlson, Kara M. Hoar, Deborah R. Wysong, Robert Gross, Mark Manfredi, Douglas Bowman, Charles E. DeZiel, Vaishali Shinde and Claudia Rabino and has published in prestigious journals such as Nucleic Acids Research, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Arijit Chakravarty

46 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
Arijit Chakravarty United States 17 691 522 458 109 97 50 1.2k
Kentaro Bandobashi Japan 16 520 0.8× 277 0.5× 419 0.9× 80 0.7× 81 0.8× 33 1.1k
Erin L. Sausville United States 5 473 0.7× 138 0.3× 186 0.4× 98 0.9× 216 2.2× 6 976
Tamotsu Sudo Japan 19 528 0.8× 183 0.4× 466 1.0× 33 0.3× 25 0.3× 57 1.5k
Eigil Kjeldsen Denmark 27 1.7k 2.5× 87 0.2× 670 1.5× 74 0.7× 38 0.4× 99 2.6k
Alain Piché Canada 27 994 1.4× 121 0.2× 680 1.5× 45 0.4× 112 1.2× 57 1.9k
Jaqueline Carvalho de Oliveira Brazil 20 780 1.1× 83 0.2× 146 0.3× 38 0.3× 59 0.6× 71 1.1k
S E Mirski Canada 21 934 1.4× 53 0.1× 762 1.7× 70 0.6× 99 1.0× 28 1.3k
Laura Lawrie United Kingdom 14 772 1.1× 144 0.3× 161 0.4× 23 0.2× 21 0.2× 14 1.1k
Aymone Gurtner Italy 26 1.5k 2.2× 158 0.3× 599 1.3× 20 0.2× 29 0.3× 42 2.0k
Christian Posch Austria 23 714 1.0× 84 0.2× 575 1.3× 26 0.2× 25 0.3× 81 1.5k

Countries citing papers authored by Arijit Chakravarty

Since Specialization
Citations

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

Fields of papers citing papers by Arijit Chakravarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arijit Chakravarty

This figure shows the co-authorship network connecting the top 25 collaborators of Arijit Chakravarty. A scholar is included among the top collaborators of Arijit Chakravarty 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 Arijit Chakravarty. Arijit Chakravarty 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.
Yuan, Lin, Meghana Kulkarni, Evan L. Chiswick, et al.. (2025). A novel approach for first‐in‐human dose selection using population dose–response modelling to find a minimum anticipated biological effect level. British Journal of Clinical Pharmacology. 91(9). 2555–2566.
2.
3.
Chakravarty, Arijit, et al.. (2024). Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface. Journal of Computer-Aided Molecular Design. 38(1). 6–6. 2 indexed citations
4.
Suman, Julie, et al.. (2023). On a model-based approach to improve intranasal spray targeting for respiratory viral infections. SHILAP Revista de lepidopterología. 3. 1164671–1164671. 9 indexed citations
5.
Yuan, Lin, Dean Bottino, Greg Hather, et al.. (2023). Heterogeneity in Vaccinal Immunity to SARS-CoV-2 Can Be Addressed by a Personalized Booster Strategy. Vaccines. 11(4). 806–806. 2 indexed citations
6.
Egeren, Debra Van, Diane Joseph‐McCarthy, Laura F. White, et al.. (2022). No magic bullet: Limiting in-school transmission in the face of variable SARS-CoV-2 viral loads. Frontiers in Public Health. 10. 941773–941773. 3 indexed citations
7.
Bottino, Dean, et al.. (2021). Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection. PubMed. 4(3). 144–148. 3 indexed citations
8.
Egeren, Debra Van, Bruce R. Zetter, Michael S. Rogers, et al.. (2021). Risk of rapid evolutionary escape from biomedical interventions targeting SARS-CoV-2 spike protein. PLoS ONE. 16(4). e0250780–e0250780. 47 indexed citations
9.
Egeren, Debra Van, et al.. (2021). Rapid relaxation of pandemic restrictions after vaccine rollout favors growth of SARS-CoV-2 variants: A model-based analysis. PLoS ONE. 16(11). e0258997–e0258997. 6 indexed citations
10.
Egeren, Debra Van, et al.. (2021). Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure. Scientific Reports. 11(1). 22630–22630. 13 indexed citations
11.
Bottino, Dean, Jilai Zhou, Chirag Patel, et al.. (2019). Dose Optimization for Anticancer Drug Combinations: Maximizing Therapeutic Index via Clinical Exposure-Toxicity/Preclinical Exposure-Efficacy Modeling. Clinical Cancer Research. 25(22). 6633–6643. 17 indexed citations
12.
Gaipov, Abduzhappar, Christopher Jackson, Manish Talwar, et al.. (2019). Association Between Serum Prealbumin Level and Outcomes in Prevalent Kidney Transplant Recipients. Journal of Renal Nutrition. 29(3). 188–195. 9 indexed citations
13.
Johnson, Kaitlyn E., Jackson Burton, Dougľas R. White, et al.. (2019). Directional inconsistency between Response Evaluation Criteria in Solid Tumors (RECIST) time to progression and response speed and depth. European Journal of Cancer. 109. 196–203. 7 indexed citations
14.
Huck, Jessica J., Mengkun Zhang, Jerome T. Mettetal, et al.. (2014). Translational Exposure–Efficacy Modeling to Optimize the Dose and Schedule of Taxanes Combined with the Investigational Aurora A Kinase Inhibitor MLN8237 (Alisertib). Molecular Cancer Therapeutics. 13(9). 2170–2183. 27 indexed citations
15.
Driscoll, Denise L., Arijit Chakravarty, Doug Bowman, et al.. (2014). Plk1 Inhibition Causes Post-Mitotic DNA Damage and Senescence in a Range of Human Tumor Cell Lines. PLoS ONE. 9(11). e111060–e111060. 45 indexed citations
16.
Palani, Santhosh, Jessica J. Huck, Mengkun Zhang, et al.. (2013). Preclinical pharmacokinetic/pharmacodynamic/efficacy relationships for alisertib, an investigational small-molecule inhibitor of Aurora A kinase. Cancer Chemotherapy and Pharmacology. 72(6). 1255–1264. 19 indexed citations
17.
Manfredi, Mark, Jeffrey Ecsedy, Arijit Chakravarty, et al.. (2011). Characterization of Alisertib (MLN8237), an Investigational Small-Molecule Inhibitor of Aurora A Kinase Using Novel In Vivo Pharmacodynamic Assays. Clinical Cancer Research. 17(24). 7614–7624. 242 indexed citations
18.
Huck, Jessica J., Arijit Chakravarty, Yu Li, et al.. (2007). Preclinical PK/PD/Efficacy relationship of MLN8054, a small molecule Aurora A kinase inhibitor. Molecular Cancer Therapeutics. 6. 2 indexed citations
19.
Carlson, Jonathan M., Arijit Chakravarty, Charles E. DeZiel, & Robert Gross. (2007). SCOPE: a web server for practical de novo motif discovery. Nucleic Acids Research. 35(Web Server). W259–W264. 88 indexed citations
20.
Chakravarty, Arijit, Louisa Howard, & Duane A. Compton. (2004). A Mechanistic Model for the Organization of Microtubule Asters by Motor and Non-Motor Proteins in a Mammalian Mitotic Extract. Molecular Biology of the Cell. 15(5). 2116–2132. 38 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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