Abhijit Chakraborty

3.9k total citations · 1 hit paper
100 papers, 2.5k citations indexed

About

Abhijit Chakraborty is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Abhijit Chakraborty has authored 100 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Oncology, 26 papers in Molecular Biology and 17 papers in Immunology. Recurrent topics in Abhijit Chakraborty's work include Advanced Breast Cancer Therapies (8 papers), CAR-T cell therapy research (8 papers) and Chronic Lymphocytic Leukemia Research (7 papers). Abhijit Chakraborty is often cited by papers focused on Advanced Breast Cancer Therapies (8 papers), CAR-T cell therapy research (8 papers) and Chronic Lymphocytic Leukemia Research (7 papers). Abhijit Chakraborty collaborates with scholars based in United States, India and Switzerland. Abhijit Chakraborty's co-authors include William J. Jusko, Wojciech Krzyżański, Gary Balas, Peter Seiler, Stacey Tannenbaum, Abhishek Shankar, Sandip Kumar Roy, Christiane Rordorf, Vincent Ribrag and Geoffrey I. Shapiro and has published in prestigious journals such as Circulation, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Abhijit Chakraborty

87 papers receiving 2.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Convergence of evolving artificial intelligence and machine learning techniques in precision oncology

2025 52 citations Elena Fountzilas, Tillman Pearce et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Abhijit Chakraborty United States	26	874	808	484	414	306	100	2.5k
Xuefeng Wang China	28	680 0.8×	854 1.1×	253 0.5×	434 1.0×	242 0.8×	179	2.4k
Thomas Streichert Germany	34	594 0.7×	1.2k 1.5×	242 0.5×	341 0.8×	154 0.5×	136	3.8k
Andrew C. Hooker Sweden	21	543 0.6×	559 0.7×	450 0.9×	234 0.6×	176 0.6×	109	3.8k
Maria Fiammetta Romano Italy	32	613 0.7×	1.3k 1.6×	271 0.6×	609 1.5×	135 0.4×	155	3.0k
Liping Du China	34	581 0.7×	897 1.1×	498 1.0×	452 1.1×	332 1.1×	172	4.0k
Jie Xiong China	29	562 0.6×	1.4k 1.7×	311 0.6×	436 1.1×	117 0.4×	128	3.2k
John P. Dowling Australia	38	918 1.1×	1.2k 1.5×	824 1.7×	749 1.8×	194 0.6×	128	4.5k
Yaning Wang United States	29	591 0.7×	769 1.0×	348 0.7×	373 0.9×	87 0.3×	117	3.4k
Lu Tang China	29	636 0.7×	1.3k 1.6×	533 1.1×	520 1.3×	142 0.5×	107	3.4k
Xiaohu Zheng China	22	742 0.8×	946 1.2×	303 0.6×	989 2.4×	157 0.5×	41	4.2k

Countries citing papers authored by Abhijit Chakraborty

Since Specialization

Citations

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

Fields of papers citing papers by Abhijit Chakraborty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhijit Chakraborty

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

All Works

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20 of 20 papers shown

Shankar, Abhishek, et al.. (2025). Exploring the potential link between human papillomavirus infection and coronary artery disease: a review of shared pathways and mechanisms. Molecular and Cellular Biochemistry. 480(7). 3971–3994. 2 indexed citations

Tsimberidou, Apostolia M., Farshid Dayyani, David Sommerhalder, et al.. (2025). Phase 1 study of zavondemstat (TACH101), a first-in-class KDM4 inhibitor, in patients with advanced solid tumors. The Oncologist. 30(7).

Fountzilas, Elena, Tillman Pearce, Mehmet A. Baysal, Abhijit Chakraborty, & Apostolia M. Tsimberidou. (2025). Convergence of evolving artificial intelligence and machine learning techniques in precision oncology. npj Digital Medicine. 8(1). 75–75. 52 indexed citations breakdown →

Valdez, Benigno C., Apostolia M. Tsimberidou, Bin Yuan, et al.. (2024). Synergistic Cytotoxicity of Histone Deacetylase and Poly-ADP Ribose Polymerase Inhibitors and Decitabine in Breast and Ovarian Cancer Cells: Implications for Novel Therapeutic Combinations. International Journal of Molecular Sciences. 25(17). 9241–9241. 2 indexed citations

Ji, Yan, Hilmar Schiller, Michelle Quinlan, et al.. (2024). Use of Pharmacokinetic and Pharmacodynamic Data to Develop the CDK4/6 Inhibitor Ribociclib for Patients with Advanced Breast Cancer. Clinical Pharmacokinetics. 63(2). 155–170. 2 indexed citations

Tsimberidou, Apostolia M., Mehmet A. Baysal, Abhijit Chakraborty, & Börje S. Andersson. (2023). Autologous engineered T cell receptor therapy in advanced cancer. Human Vaccines & Immunotherapeutics. 19(3). 2290356–2290356. 4 indexed citations

Mishra, Abhinava K., Ashna Gupta, Gunjan Dagar, et al.. (2023). CAR-T-Cell Therapy in Multiple Myeloma: B-Cell Maturation Antigen (BCMA) and Beyond. Vaccines. 11(11). 1721–1721. 26 indexed citations

Ikeda, Yuichi & Abhijit Chakraborty. (2023). Hodge Decomposition of the Remittance Network on the XRP Ledger in the Price Hike of January 2018. 3 indexed citations

Chakraborty, Abhijit, et al.. (2023). Quantum computing with trapped ions: a beginner’s guide. European Journal of Physics. 45(1). 13001–13001.

10.

Ji, Yan, Michelle Quinlan, Paolo Serra, et al.. (2023). Justifying Ribociclib Dose in Patients with Advanced Breast Cancer with Renal Impairment Based on PK, Safety, and Efficacy Data: An Innovative Approach Integrating Data from a Dedicated Renal Impairment Study and Oncology Clinical Trials. Clinical Pharmacokinetics. 62(3). 493–504. 6 indexed citations

11.

Chakraborty, Abhijit, et al.. (2023). Efficacy and safety of hair serum containing Greyverse, EUK 134 and Amisol trio in premature greying of hair. International Journal of Research in Medical Sciences. 11(9). 3396–3401. 1 indexed citations

12.

Chakraborty, Abhijit, Yanming Li, Chen Zhang, et al.. (2023). Epigenetic Induction of Smooth Muscle Cell Phenotypic Alterations in Aortic Aneurysms and Dissections. Circulation. 148(12). 959–977. 65 indexed citations

13.

Aziz, Faisal, et al.. (2022). Relevance of miR-223 as Potential Diagnostic and Prognostic Markers in Cancer. Biology. 11(2). 249–249. 17 indexed citations

14.

Zhang, Chen, Yanming Li, Abhijit Chakraborty, et al.. (2022). Aortic Stress Activates an Adaptive Program in Thoracic Aortic Smooth Muscle Cells That Maintains Aortic Strength and Protects Against Aneurysm and Dissection in Mice. Arteriosclerosis Thrombosis and Vascular Biology. 43(2). 234–252. 20 indexed citations

15.

Mukhopadhyay, Pradip, et al.. (2021). Periodontal Disease in Type 1 Diabetes Mellitus: Influence of Pubertal Stage and Glycemic Control. Endocrine Practice. 27(8). 765–768. 9 indexed citations

16.

Lee, Kun Y., Ke Yao, Seung Ho Shin, et al.. (2020). GSK3β-Mediated Expression of CUG-Translated WT1 Is Critical for Tumor Progression. Cancer Research. 81(4). 945–955. 7 indexed citations

17.

Infante, Jeffrey R., Philippe A. Cassier, John F. Gerecitano, et al.. (2016). A Phase I Study of the Cyclin-Dependent Kinase 4/6 Inhibitor Ribociclib (LEE011) in Patients with Advanced Solid Tumors and Lymphomas. Clinical Cancer Research. 22(23). 5696–5705. 237 indexed citations

18.

Chakraborty, Abhijit, et al.. (2016). Determinants of lymph node status in women with breast cancer. The Indian Journal of Medical Research. 143(Suppl 1). S45–S51. 10 indexed citations

19.

Chakraborty, Abhijit, et al.. (2012). Frequency of 5382insC mutation of BRCA1 gene among breast cancer patients: an experience from Eastern India. Familial Cancer. 12(3). 489–495. 8 indexed citations

20.

Chakraborty, Abhijit & William J. Jusko. (2002). Pharmacodynamic Interaction of Recombinant Human Interleukin-10 and Prednisolone Using in vitro Whole Blood Lymphocyte Proliferation. Journal of Pharmaceutical Sciences. 91(5). 1334–1342. 48 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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