Naval Daver

33.4k total citations · 6 hit papers
622 papers, 14.5k citations indexed

About

Naval Daver is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Naval Daver has authored 622 papers receiving a total of 14.5k indexed citations (citations by other indexed papers that have themselves been cited), including 523 papers in Hematology, 252 papers in Genetics and 190 papers in Molecular Biology. Recurrent topics in Naval Daver's work include Acute Myeloid Leukemia Research (433 papers), Chronic Myeloid Leukemia Treatments (192 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (140 papers). Naval Daver is often cited by papers focused on Acute Myeloid Leukemia Research (433 papers), Chronic Myeloid Leukemia Treatments (192 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (140 papers). Naval Daver collaborates with scholars based in United States, United Kingdom and Italy. Naval Daver's co-authors include Hagop M. Kantarjian, Farhad Ravandi, Tapan M. Kadia, Guillermo Garcia‐Manero, Marina Konopleva, Jörge E. Cortes, Elias Jabbour, Gautam Borthakur, Courtney D. DiNardo and Naveen Pemmaraju and has published in prestigious journals such as Nature Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Naval Daver

584 papers receiving 14.4k citations

Hit Papers

Chimeric antigen receptor... 2017 2026 2020 2023 2017 2019 2021 2020 2022 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Naval Daver 9.2k 5.9k 4.5k 3.4k 2.2k 622 14.5k
Gert J. Ossenkoppele 8.6k 0.9× 4.4k 0.7× 2.8k 0.6× 2.8k 0.8× 1.9k 0.9× 279 12.3k
Tapan M. Kadia 9.8k 1.1× 5.4k 0.9× 2.7k 0.6× 3.9k 1.1× 1.1k 0.5× 778 13.2k
Courtney D. DiNardo 10.1k 1.1× 6.6k 1.1× 2.6k 0.6× 3.3k 1.0× 1.2k 0.5× 628 13.5k
Marilyn L. Slovak 6.9k 0.7× 4.4k 0.7× 4.0k 0.9× 2.3k 0.7× 1.0k 0.5× 152 11.7k
Hervé Dombret 13.5k 1.5× 7.2k 1.2× 4.1k 0.9× 3.7k 1.1× 1.9k 0.9× 377 18.9k
John F. DiPersio 12.0k 1.3× 6.4k 1.1× 5.9k 1.3× 3.2k 0.9× 5.1k 2.3× 596 20.8k
Ghulam J. Mufti 7.7k 0.8× 4.0k 0.7× 1.8k 0.4× 2.9k 0.9× 2.2k 1.0× 268 11.2k
Oliver G. Ottmann 10.4k 1.1× 4.9k 0.8× 4.0k 0.9× 5.0k 1.5× 2.4k 1.1× 372 16.1k
Cheryl L. Willman 12.3k 1.3× 8.4k 1.4× 4.6k 1.0× 2.8k 0.8× 1.7k 0.8× 235 20.5k
Marcos González 8.1k 0.9× 5.3k 0.9× 2.9k 0.7× 4.1k 1.2× 2.5k 1.1× 376 14.1k

Countries citing papers authored by Naval Daver

Since Specialization
Citations

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

Fields of papers citing papers by Naval Daver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naval Daver

This figure shows the co-authorship network connecting the top 25 collaborators of Naval Daver. A scholar is included among the top collaborators of Naval Daver 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 Naval Daver. Naval Daver 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.
Fiskus, Warren, Christopher P. Mill, Christine Birdwell, et al.. (2025). Preclinical activity of investigational menin inhibitor DSP-5336 (Enzomenib)-based combinations against MLL1-rearranged (MLL-r) or mutant-NPM1 AML models. Blood. 146(Supplement 1). 1497–1497.
2.
Zeidan, Amer M., Anthony S. Stein, Johanna Rimpiläinen, et al.. (2025). Efficacy, molecular and translational analysis of TP53-mutated HR-MDS with bexmarilimab and azacitidine: Updated results from the bexmab Phase 1/2 study. Blood. 146(Supplement 1). 236–236. 1 indexed citations
5.
Mill, Christopher P., Warren Fiskus, Christine Birdwell, et al.. (2024). ASXL1 Mutations in AML Are Associated with a Distinct Epigenetic State Which Highlights Vulnerabilities to Specific Epigenetic-Targeted Agents. Blood. 144(Supplement 1). 1349–1349. 1 indexed citations
6.
Mohamed, Shehab, Naveen Pemmaraju, Tapan M. Kadia, et al.. (2024). BRAF mutation in myeloid neoplasm: incidences and clinical outcomes. Leukemia & lymphoma. 65(9). 1344–1349. 1 indexed citations
7.
Daver, Naval, Abhishek Maiti, David A. Sallman, et al.. (2024). A first-in-human phase 1, multicenter, open-label study of CB-012, a next-generation CRISPR-edited allogeneic anti-CLL-1 CAR-T cell therapy for adults with relapsed/refractory acute myeloid leukemia (AMpLify).. Journal of Clinical Oncology. 42(16_suppl). TPS6586–TPS6586. 5 indexed citations
9.
Jabbour, Elias, Fadi Haddad, Koji Sasaki, et al.. (2024). Combination of dasatinib and venetoclax in newly diagnosed chronic phase chronic myeloid leukemia. Cancer. 130(15). 2652–2659. 8 indexed citations
11.
Bataller, Álex, Alexandre Bazinet, Courtney D. DiNardo, et al.. (2023). Prognostic risk signature in patients with acute myeloid leukemia treated with hypomethylating agents and venetoclax. Blood Advances. 8(4). 927–935. 36 indexed citations
12.
Fan, Huihui, Feng Wang, Andy G.X. Zeng, et al.. (2023). Single-cell chromatin accessibility profiling of acute myeloid leukemia reveals heterogeneous lineage composition upon therapy-resistance. Communications Biology. 6(1). 765–765. 11 indexed citations
13.
Daver, Naval, Abhishek Maiti, Tapan M. Kadia, et al.. (2022). TP53 -Mutated Myelodysplastic Syndrome and Acute Myeloid Leukemia: Biology, Current Therapy, and Future Directions. Cancer Discovery. 12(11). 2516–2529. 83 indexed citations
14.
Daver, Naval, Alexander E. Perl, Joseph Maly, et al.. (2022). Venetoclax Plus Gilteritinib for FLT3-Mutated Relapsed/Refractory Acute Myeloid Leukemia. Journal of Clinical Oncology. 40(35). 4048–4059. 123 indexed citations breakdown →
15.
Hammond, Danielle, Tapan M. Kadia, Courtney D. DiNardo, et al.. (2021). Clinical Characteristics and Contemporary Outcomes of Acute Myeloid Leukemia Evolving from Chronic Myelomonocytic Leukemia. Blood. 138(Supplement 1). 1224–1224. 1 indexed citations
16.
Shah, Mithun Vinod, Rima M. Saliba, Ankur Varma, et al.. (2021). Allogeneic stem cell transplant for patients with myeloproliferative neoplasms in blast phase: improving outcomes in the recent era. British Journal of Haematology. 193(5). 1004–1008. 8 indexed citations
17.
Alfayez, Musaad, et al.. (2019). Midostaurin In Acute Myeloid Leukemia: An Evidence-Based Review And Patient Selection. SHILAP Revista de lepidopterología. 1 indexed citations
18.
Sasaki, Koji, Hagop M. Kantarjian, Tapan M. Kadia, et al.. (2019). Sorafenib plus intensive chemotherapy improves survival in patients with newly diagnosed, FLT3‐internal tandem duplication mutation–positive acute myeloid leukemia. Cancer. 125(21). 3755–3766. 36 indexed citations
19.
Roboz, Gail J., Hagop M. Kantarjian, Karen Yee, et al.. (2017). Dose, schedule, safety, and efficacy of guadecitabine in relapsed or refractory acute myeloid leukemia. Cancer. 124(2). 325–334. 49 indexed citations
20.
Nazha, Aziz, Joseph D. Khoury, Raajit K. Rampal, & Naval Daver. (2015). Fibrogenesis in Primary Myelofibrosis: Diagnostic, Clinical, and Therapeutic Implications. The Oncologist. 20(10). 1154–1160. 13 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026