Nitin Jain

23.9k total citations · 1 hit paper
464 papers, 9.7k citations indexed

About

Nitin Jain is a scholar working on Genetics, Hematology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Nitin Jain has authored 464 papers receiving a total of 9.7k indexed citations (citations by other indexed papers that have themselves been cited), including 258 papers in Genetics, 218 papers in Hematology and 174 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Nitin Jain's work include Chronic Lymphocytic Leukemia Research (232 papers), Acute Lymphoblastic Leukemia research (173 papers) and Chronic Myeloid Leukemia Treatments (144 papers). Nitin Jain is often cited by papers focused on Chronic Lymphocytic Leukemia Research (232 papers), Acute Lymphoblastic Leukemia research (173 papers) and Chronic Myeloid Leukemia Treatments (144 papers). Nitin Jain collaborates with scholars based in United States, Israel and India. Nitin Jain's co-authors include Hagop M. Kantarjian, William G. Wierda, Elias Jabbour, Farhad Ravandi, Naval Daver, Guillermo Garcia‐Manero, Jörge E. Cortes, Marina Konopleva, Zeev Estrov and Alessandra Ferrajoli and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Nitin Jain

423 papers receiving 9.6k citations

Hit Papers

Chimeric antigen receptor T-cell therapy — assessment and... 2017 2026 2020 2023 2017 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nitin Jain United States 49 3.8k 3.5k 3.2k 2.4k 2.3k 464 9.7k
Carlos E. Bueso‐Ramos United States 59 3.0k 0.8× 6.0k 1.7× 4.3k 1.3× 5.8k 2.4× 1.8k 0.8× 386 14.7k
Marilyn L. Slovak United States 46 4.0k 1.0× 6.9k 2.0× 2.3k 0.7× 4.4k 1.9× 2.8k 1.2× 152 11.7k
Tomoki Naoe Japan 56 2.9k 0.8× 7.9k 2.3× 2.7k 0.9× 8.1k 3.4× 2.5k 1.1× 352 15.9k
David F. Claxton United States 40 2.6k 0.7× 5.6k 1.6× 1.5k 0.5× 2.8k 1.2× 1.4k 0.6× 195 9.1k
Jonathan E. Kolitz United States 61 2.3k 0.6× 6.6k 1.9× 6.7k 2.1× 5.2k 2.2× 2.2k 1.0× 256 14.4k
Gert J. Ossenkoppele Netherlands 53 2.8k 0.7× 8.6k 2.5× 2.8k 0.9× 4.4k 1.8× 2.3k 1.0× 279 12.3k
Jane L. Liesveld United States 47 2.3k 0.6× 3.7k 1.1× 1.4k 0.4× 2.8k 1.2× 759 0.3× 252 8.3k
Daniel J. DeAngelo United States 60 4.3k 1.1× 9.0k 2.6× 3.9k 1.2× 6.2k 2.6× 4.3k 1.9× 444 16.3k
Susan M. Blaney United States 63 3.3k 0.9× 1.2k 0.3× 2.5k 0.8× 5.0k 2.1× 1.3k 0.6× 267 11.4k
Oliver G. Ottmann Germany 62 4.0k 1.0× 10.4k 3.0× 5.0k 1.6× 4.9k 2.1× 3.3k 1.4× 372 16.1k

Countries citing papers authored by Nitin Jain

Since Specialization
Citations

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

Fields of papers citing papers by Nitin Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nitin Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Nitin Jain. A scholar is included among the top collaborators of Nitin Jain 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 Nitin Jain. Nitin Jain 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.
Short, Nicholas J., Elias Jabbour, Walid Macaron, et al.. (2025). Prognostic impact of early NGS MRD dynamics and cytomolecular risk in newly diagnosed B-cell ALL. Blood Cancer Journal. 15(1). 169–169.
2.
Ledesma, Celina, Nitin Jain, Priti Tewari, et al.. (2024). Allogeneic Hematopoietic Stem Cell Transplantation Following CAR T Therapy in Relapsed/Refractory Acute Lymphoblastic Leukemia. Blood. 144(Supplement 1). 2810–2810. 1 indexed citations
3.
Bataller, Álex, Alexandre Bazinet, Gautam Borthakur, et al.. (2024). Phase Ib/II Study of CPX-351 Plus Venetoclax in Patients with Relapsed/Refractory Acute Myeloid Leukemia (AML). Blood. 144(Supplement 1). 4272–4272.
4.
Bataller, Álex, Hagop M. Kantarjian, Alexandre Bazinet, et al.. (2024). Phase II Study of Cladribine with Low Dose Cytarabine and Venetoclax Alternating with Azacytidine and Venetoclax for Newly Diagnosed Acute Myeloid Leukemia. Blood. 144(Supplement 1). 56–56. 3 indexed citations
5.
Shi, Chunhua, Guojun Yang, Qing Shi, et al.. (2023). Preclinical development of 1B7/CD3, a novel anti-TSLPR bispecific antibody that targets CRLF2-rearranged Ph-like B-ALL. Leukemia. 37(10). 2006–2016. 6 indexed citations
7.
Gordon, Max J., Jade Jones, Binsah George, et al.. (2023). Long‐term outcomes in patients with chronic lymphocytic leukemia treated with ibrutinib: Focus on hypertension and cardiovascular toxicity. Cancer. 129(14). 2192–2200. 10 indexed citations
9.
Thompson, Philip A., Michael J. Keating, Alessandra Ferrajoli, et al.. (2023). Venetoclax consolidation in high-risk CLL treated with ibrutinib for ≥1 year achieves a high rate of undetectable MRD. Leukemia. 37(7). 1444–1453. 2 indexed citations
10.
Jabbour, Elias, Koji Sasaki, Fadi Haddad, et al.. (2023). The outcomes of patients with chronic myeloid leukemia treated with third‐line BCR::ABL1 tyrosine kinase inhibitors. American Journal of Hematology. 98(4). 658–665. 15 indexed citations
11.
Chin, Hou-Man, et al.. (2022). Digital synchronization for continuous-variable quantum key distribution. Quantum Science and Technology. 7(4). 45006–45006.
12.
Guo, Xiaojie, et al.. (2022). 40 km fiber transmission of squeezed light measured with a real local oscillator. Quantum Science and Technology. 7(4). 45003–45003. 14 indexed citations
13.
Sasaki, Koji, Elias Jabbour, Nicholas J. Short, et al.. (2021). Acute lymphoblastic leukemia: A population‐based study of outcome in the United States based on the surveillance, epidemiology, and end results (SEER) database, 19802017. American Journal of Hematology. 96(6). 650–658. 79 indexed citations
14.
Richard‐Carpentier, Guillaume, Hagop M. Kantarjian, Guilin Tang, et al.. (2021). Outcomes of acute lymphoblastic leukemia with KMT2A (MLL) rearrangement: the MD Anderson experience. Blood Advances. 5(23). 5415–5419. 25 indexed citations
17.
Flinn, Ian W., Susan O’Brien, Brad S. Kahl, et al.. (2017). Duvelisib, a novel oral dual inhibitor of PI3K-δ,γ, is clinically active in advanced hematologic malignancies. Blood. 131(8). 877–887. 183 indexed citations
18.
Rozovski, Uri, David Harris, Ping Li, et al.. (2017). Constitutive Phosphorylation of STAT3 by the CK2–BLNK–CD5 Complex. Molecular Cancer Research. 15(5). 610–618. 23 indexed citations
19.
Khan, Maliha, Hagop M. Kantarjian, Jing Ning, et al.. (2017). Response and Outcomes of Third-Line Tyrosine Kinase Inhibitor Therapy on Patients with Chronic Phase Chronic Myeloid Leukemia. Blood. 130. 2882–2882. 1 indexed citations
20.
Rozovski, Uri, Srđana Grgurević, Carlos Bueso-Ramos, et al.. (2015). Aberrant LPL Expression, Driven by STAT3, Mediates Free Fatty Acid Metabolism in CLL Cells. Molecular Cancer Research. 13(5). 944–953. 69 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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