Maya C. André

1.4k total citations
30 papers, 925 citations indexed

About

Maya C. André is a scholar working on Immunology, Oncology and Hematology. According to data from OpenAlex, Maya C. André has authored 30 papers receiving a total of 925 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 11 papers in Oncology and 6 papers in Hematology. Recurrent topics in Maya C. André's work include Immune Cell Function and Interaction (12 papers), CAR-T cell therapy research (9 papers) and T-cell and B-cell Immunology (7 papers). Maya C. André is often cited by papers focused on Immune Cell Function and Interaction (12 papers), CAR-T cell therapy research (9 papers) and T-cell and B-cell Immunology (7 papers). Maya C. André collaborates with scholars based in Germany, Switzerland and United States. Maya C. André's co-authors include Rupert Handgretinger, Peter Lang, Udo F. Hartwig, Martina Konantz, Claudia Lengerke, Tuğçe B. Balcı, Graham Dellaire, Jason N. Berman, Andreas Hombach and Hinrich Abken and has published in prestigious journals such as Blood, The Journal of Immunology and PLoS ONE.

In The Last Decade

Maya C. André

29 papers receiving 910 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maya C. André Germany 17 441 355 275 211 105 30 925
Yi Zeng United States 19 927 2.1× 425 1.2× 524 1.9× 223 1.1× 117 1.1× 30 1.3k
Leonardo Mirandola United States 20 512 1.2× 439 1.2× 606 2.2× 188 0.9× 28 0.3× 58 1.1k
Jean A. Yared United States 15 206 0.5× 463 1.3× 205 0.7× 173 0.8× 27 0.3× 66 838
Carla Guenther Finland 9 292 0.7× 189 0.5× 312 1.1× 97 0.5× 69 0.7× 14 841
Shigeto Kawai Japan 14 281 0.6× 188 0.5× 339 1.2× 152 0.7× 34 0.3× 28 837
Curtis J. Henry United States 16 433 1.0× 213 0.6× 272 1.0× 112 0.5× 25 0.2× 49 887
Chandra Sekhar Boddupalli United States 13 665 1.5× 492 1.4× 328 1.2× 233 1.1× 90 0.9× 19 1.3k
Anthony Cruz United States 14 579 1.3× 269 0.8× 695 2.5× 60 0.3× 58 0.6× 21 1.1k
Taina Jaatinen Finland 17 223 0.5× 105 0.3× 332 1.2× 185 0.9× 53 0.5× 28 750
Anja Krippner‐Heidenreich United Kingdom 21 408 0.9× 229 0.6× 565 2.1× 56 0.3× 50 0.5× 32 1.0k

Countries citing papers authored by Maya C. André

Since Specialization
Citations

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

Fields of papers citing papers by Maya C. André

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya C. André. 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 Maya C. André. The network helps show where Maya C. André may publish in the future.

Co-authorship network of co-authors of Maya C. André

This figure shows the co-authorship network connecting the top 25 collaborators of Maya C. André. A scholar is included among the top collaborators of Maya C. André 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 Maya C. André. Maya C. André 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.
Blanchard‐Rohner, Géraldine, Maya C. André, Serge Grazioli, et al.. (2024). COVID-19 Vaccine Acceptance Among Parents of Children With Multisystem Inflammatory Syndrome in Children. The Pediatric Infectious Disease Journal. 43(4). 361–364.
2.
3.
André, Maya C., et al.. (2023). Optimized flow cytometry panel for the detection and analysis of human tumor-induced memory-like NK cells. Journal of Immunological Methods. 515. 113439–113439. 5 indexed citations
4.
5.
Prader, Seraina, Nicole Ritz, Frédéric Baleydier, et al.. (2021). X-Linked Lymphoproliferative Disease Mimicking Multisystem Inflammatory Syndrome in Children—A Case Report. Frontiers in Pediatrics. 9. 691024–691024. 3 indexed citations
6.
André, Maya C., et al.. (2018). From bench to bedside: Exploiting memory NK cell responses to leukemia. 2(1). e28–e28. 2 indexed citations
7.
André, Maya C. & Jürg Hammer. (2018). Life-Threatening Accidental Intravenous Epinephrine Overdose in a 12-Year-Old Boy. Pediatric Emergency Care. 35(6). e110–e112. 7 indexed citations
8.
Handgretinger, Rupert, Peter Lang, & Maya C. André. (2016). Exploitation of natural killer cells for the treatment of acute leukemia. Blood. 127(26). 3341–3349. 118 indexed citations
9.
André, Maya C., Josef Leibold, Philaretos C. Kousis, et al.. (2016). An Fc-optimized CD133 antibody for induction of NK cell reactivity against myeloid leukemia. Leukemia. 31(2). 459–469. 48 indexed citations
10.
Vick, Binje, Michela Carlet, Christina Krupka, et al.. (2015). An Advanced Preclinical Mouse Model for Acute Myeloid Leukemia Using Patients' Cells of Various Genetic Subgroups and In Vivo Bioluminescence Imaging. PLoS ONE. 10(3). e0120925–e0120925. 48 indexed citations
11.
Steinbacher, Julia, Benjamin Joachim Schmiedel, Alexander Steinle, et al.. (2014). An Fc‐optimized NKG2D‐immunoglobulin G fusion protein for induction of natural killer cell reactivity against leukemia. International Journal of Cancer. 136(5). 1073–1084. 27 indexed citations
12.
Bugl, Stefanie, Stefan Wirths, Markus P. Radsak, et al.. (2012). Steady-state neutrophil homeostasis is dependent on TLR4/TRIF signaling. Blood. 121(5). 723–733. 78 indexed citations
13.
Gille, Christian, Thorsten Orlikowsky, Udo F. Hartwig, et al.. (2012). Monocytes derived from humanized neonatal NOD/SCID/IL2Rγnull mice are phenotypically immature and exhibit functional impairments. Human Immunology. 73(4). 346–354. 42 indexed citations
14.
Konantz, Martina, Tuğçe B. Balcı, Udo F. Hartwig, et al.. (2012). Zebrafish xenografts as a tool for in vivo studies on human cancer. Annals of the New York Academy of Sciences. 1266(1). 124–137. 171 indexed citations
15.
André, Maya C., et al.. (2011). Impaired tumor rejection by memory CD8 T cells in mice with NKG2D dysfunction. International Journal of Cancer. 131(7). 1601–1610. 17 indexed citations
16.
Stebut, Esther von, Diana Wolff, Eva Wagner, et al.. (2011). Human Epidermal Langerhans Cells Replenish Skin Xenografts and Are Depleted by Alloreactive T Cells In Vivo. The Journal of Immunology. 187(3). 1142–1149. 14 indexed citations
17.
Schäfer, Iris, Maya C. André, Gunter Kerst, et al.. (2011). High Proportion of Leukemic Stem Cells at Diagnosis Is Correlated with Unfavorable Prognosis in Childhood Acute Myeloid Leukemia. Pediatric Hematology and Oncology. 28(2). 91–99. 33 indexed citations
18.
André, Maya C., Annika Erbacher, Christian Gille, et al.. (2010). Long-Term Human CD34+ Stem Cell-Engrafted Nonobese Diabetic/SCID/IL-2Rγnull Mice Show Impaired CD8+ T Cell Maintenance and a Functional Arrest of Immature NK Cells. The Journal of Immunology. 185(5). 2710–2720. 65 indexed citations
19.
Ebinger, Martin, Iris Schäfer, Maya C. André, et al.. (2010). High frequency of immature cells at diagnosis predicts high minimal residual disease level in childhood acute lymphoblastic leukemia. Leukemia Research. 34(9). 1139–1142. 21 indexed citations
20.
Janot, C., et al.. (1989). [Post-transfusion cytomegalovirus infection in premature infants weighing less than 1,500 g].. PubMed. 44(6). 471–9. 1 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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