Ivan Maillard

15.3k total citations · 2 hit papers
152 papers, 8.1k citations indexed

About

Ivan Maillard is a scholar working on Molecular Biology, Immunology and Hematology. According to data from OpenAlex, Ivan Maillard has authored 152 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Molecular Biology, 61 papers in Immunology and 44 papers in Hematology. Recurrent topics in Ivan Maillard's work include T-cell and B-cell Immunology (38 papers), Immune Cell Function and Interaction (32 papers) and Acute Myeloid Leukemia Research (25 papers). Ivan Maillard is often cited by papers focused on T-cell and B-cell Immunology (38 papers), Immune Cell Function and Interaction (32 papers) and Acute Myeloid Leukemia Research (25 papers). Ivan Maillard collaborates with scholars based in United States, Switzerland and Slovakia. Ivan Maillard's co-authors include Warren S. Pear, Jon C. Aster, Terry Fang, Avinash Bhandoola, Lanwei Xu, Olga Shestova, Arivazhagan Sambandam, James Douglas Engel, Tomonori Hosoya and Hong Sai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Medicine.

In The Last Decade

Ivan Maillard

148 papers receiving 8.0k citations

Hit Papers

Promising Survival for Pa... 2002 2026 2010 2018 2002 2011 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Ivan Maillard 3.7k 2.7k 1.5k 1.2k 811 152 8.1k
Arinobu Tojo 3.1k 0.8× 1.6k 0.6× 1.9k 1.3× 2.5k 2.1× 1.4k 1.8× 364 8.2k
Stuart H. Orkin 5.5k 1.5× 1.9k 0.7× 918 0.6× 1.5k 1.3× 677 0.8× 62 8.4k
David Allman 3.3k 0.9× 6.7k 2.4× 2.4k 1.6× 1.1k 0.9× 557 0.7× 112 11.0k
Robert Hromas 6.1k 1.6× 2.7k 1.0× 2.7k 1.8× 1.6k 1.4× 445 0.5× 207 10.4k
Jon Frampton 3.0k 0.8× 2.3k 0.9× 723 0.5× 1.6k 1.3× 558 0.7× 100 7.4k
Paul W. Kincade 3.0k 0.8× 5.4k 2.0× 1.2k 0.8× 2.0k 1.7× 657 0.8× 155 9.6k
Ashley R. Dunn 3.6k 1.0× 4.9k 1.8× 2.0k 1.3× 1.1k 0.9× 545 0.7× 101 10.0k
Kojo S.J. Elenitoba‐Johnson 3.7k 1.0× 1.2k 0.4× 2.0k 1.3× 876 0.7× 1.1k 1.4× 190 7.9k
Hiromi Iwasaki 4.3k 1.2× 3.7k 1.3× 1.7k 1.1× 3.5k 2.9× 1.1k 1.4× 170 9.1k
Nada Jabado 3.0k 0.8× 1.6k 0.6× 751 0.5× 1.1k 0.9× 2.1k 2.6× 168 7.0k

Countries citing papers authored by Ivan Maillard

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Maillard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Maillard

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Maillard. A scholar is included among the top collaborators of Ivan Maillard 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 Ivan Maillard. Ivan Maillard 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.
Kahn, Benjamin, Raymond W.S. Ng, Il‐Kyu Kim, et al.. (2025). Intrinsic Properties of the Lymph Node Render It Immunologically Susceptible to Metastasis. Cancer Discovery. 15(9). 1949–1968.
2.
3.
Lütge, Mechthild, Hung‐Wei Cheng, Angelina De Martin, et al.. (2025). Fibroblastic reticular cells form reactive myeloid cell niches in human lymph nodes. Science Immunology. 10(107). eads6820–eads6820. 4 indexed citations
4.
Liu, Yiman, Qinglan Li, Ashley Vanderbeck, et al.. (2024). Condensate-Promoting ENL Mutation Drives Tumorigenesis In Vivo Through Dynamic Regulation of Histone Modifications and Gene Expression. Cancer Discovery. 14(8). 1522–1546. 8 indexed citations
5.
Martin, Angelina De, Mechthild Lütge, Lucas Onder, et al.. (2023). PI16+ reticular cells in human palatine tonsils govern T cell activity in distinct subepithelial niches. Nature Immunology. 24(7). 1138–1148. 25 indexed citations
6.
Matthews, Andrew, Alexander E. Perl, Selina M. Luger, et al.. (2022). Real-world effectiveness of CPX-351 vs venetoclax and azacitidine in acute myeloid leukemia. Blood Advances. 6(13). 3997–4005. 53 indexed citations
7.
Gao, Xin, Chenguang Wang, Carlos Murga‐Zamalloa, et al.. (2022). Notch Signaling Promotes Mature T-Cell Lymphomagenesis. Cancer Research. 82(20). 3763–3773. 6 indexed citations
8.
Friedman, Ann, Eric Perkey, Frederick H. Allen, et al.. (2021). TPP1 mutagenesis screens unravel shelterin interfaces and functions in hematopoiesis. JCI Insight. 6(9). 7 indexed citations
9.
Gómez, Daniela, Lyndsay Avery, Nathan H. Roy, et al.. (2021). Lymphocyte egress signal sphingosine-1-phosphate promotes ERM-guided, bleb-based migration. The Journal of Cell Biology. 220(6). 21 indexed citations
10.
Jia, Wei, Jonathan C. Poe, Sarah Anand, et al.. (2021). BAFF promotes heightened BCR responsiveness and manifestations of chronic GVHD after allogeneic stem cell transplantation. Blood. 137(18). 2544–2557. 20 indexed citations
11.
Serrano‐López, Juana, Shailaja Hegde, Sachin Kumar, et al.. (2021). Inflammation rapidly recruits mammalian GMP and MDP from bone marrow into regional lymphatics. eLife. 10. 4 indexed citations
12.
Sun, Lova, Anh N. Le, Abigail Doucette, et al.. (2020). Rates of COVID-19–Related Outcomes in Cancer Compared With Noncancer Patients. JNCI Cancer Spectrum. 5(1). 27 indexed citations
13.
Perkey, Eric, Jooho Chung, Ute Koch, et al.. (2020). GCNT1-Mediated O-Glycosylation of the Sialomucin CD43 Is a Sensitive Indicator of Notch Signaling in Activated T Cells. The Journal of Immunology. 204(6). 1674–1688. 21 indexed citations
14.
Trissal, Maria, Terrence N. Wong, Juo-Chin Yao, et al.. (2018). MIR142 Loss-of-Function Mutations Derepress ASH1L to Increase HOXA Gene Expression and Promote Leukemogenesis. Cancer Research. 78(13). 3510–3521. 34 indexed citations
15.
Ropa, James, Jennifer Chase, Chenxi Shen, et al.. (2017). The AF9-Binding Domain of DOT1L Is Critical for Its Recruitment By MLL Fusion Proteins in Leukemia and Contributes to Its Functions in Normal Hematopoiesis. Blood. 130. 3785–3785. 1 indexed citations
16.
Veniaminova, Natalia A., Alicia N. Vagnozzi, Daniel Kopinke, et al.. (2013). Keratin 79 identifies a novel population of migratory epithelial cells that initiates hair canal morphogenesis and regeneration. Development. 140(24). 4870–4880. 59 indexed citations
17.
Jones, Morgan, Joshua A. Regal, Daniel N. Weinberg, et al.. (2013). Hematopoietic stem cells are acutely sensitive to Acd shelterin gene inactivation. Journal of Clinical Investigation. 124(1). 353–366. 11 indexed citations
18.
Tran, Ivy, Ashley R. Sandy, Alexis J. Carulli, et al.. (2013). Blockade of individual Notch ligands and receptors controls graft-versus-host disease. Journal of Clinical Investigation. 123(4). 1590–1604. 111 indexed citations
19.
Caruso, Sarah, Morgan Jones, Rork Kuick, et al.. (2012). Convergence of the ZMIZ1 and NOTCH1 Pathways at C-MYC in Acute T Lymphoblastic Leukemias. Cancer Research. 73(2). 930–941. 45 indexed citations
20.
Maillard, Ivan, Andrew P. Weng, Andrea C. Carpenter, et al.. (2004). Mastermind critically regulates Notch-mediated lymphoid cell fate decisions. Blood. 104(6). 1696–1702. 235 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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