Dina Schneider

3.2k total citations · 1 hit paper
67 papers, 2.0k citations indexed

About

Dina Schneider is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Dina Schneider has authored 67 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Oncology, 24 papers in Immunology and 23 papers in Molecular Biology. Recurrent topics in Dina Schneider's work include CAR-T cell therapy research (56 papers), Viral Infectious Diseases and Gene Expression in Insects (19 papers) and Virus-based gene therapy research (8 papers). Dina Schneider is often cited by papers focused on CAR-T cell therapy research (56 papers), Viral Infectious Diseases and Gene Expression in Insects (19 papers) and Virus-based gene therapy research (8 papers). Dina Schneider collaborates with scholars based in United States, Germany and France. Dina Schneider's co-authors include Boro Dropulić, Rimas J. Orentas, Marc B. Hershenson, Umadevi Sajjan, Winfried Krueger, Parameswaran Hari, Nirav N. Shah, Darong Wu, Ying Xiong and Emily Bowman and has published in prestigious journals such as Nature Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Dina Schneider

64 papers receiving 2.0k citations

Hit Papers

Bispecific anti-CD20, anti-CD19 CAR T cells for relapsed ... 2020 2026 2022 2024 2020 100 200 300

Peers

Dina Schneider
Sarah Nikiforow United States
Caridad Martinez United States
Jon Arnason United States
Marie Bleakley United States
Sadik H. Kassim United States
Siu‐Hong Ho United States
Kristin G. Anderson United States
Cecilia C.S. Yeung United States
Sarah Nikiforow United States
Dina Schneider
Citations per year, relative to Dina Schneider Dina Schneider (= 1×) peers Sarah Nikiforow

Countries citing papers authored by Dina Schneider

Since Specialization
Citations

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

Fields of papers citing papers by Dina Schneider

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dina Schneider

This figure shows the co-authorship network connecting the top 25 collaborators of Dina Schneider. A scholar is included among the top collaborators of Dina Schneider 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 Dina Schneider. Dina Schneider 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.
Shah, Nirav N., Bryon D. Johnson, Anikó Szabó, et al.. (2025). Phase I/II Study of Adaptive Manufactured Lentiviral Anti-CD20/Anti-CD19 Chimeric Antigen Receptor T Cells for Relapsed, Refractory Mantle Cell Lymphoma. Journal of Clinical Oncology. 43(20). 2285–2295. 2 indexed citations
3.
Hensen, Luca, et al.. (2024). Allogeneic CD19/CD22 CAR T-Cell Therapy for B-Cell Acute Lymphoblastic Leukemia. JAMA Oncology. 10(6). 821–821. 7 indexed citations
4.
Shah, Nirav N., Anikó Szabó, Dina Schneider, et al.. (2024). Phase 1 Study of Trispecific Anti-CD20, Anti-CD19, Anti-CD22 (CAR20.19.22) T Cells for Relapsed, Refractory B-Cell Malignancies. Blood. 144(Supplement 1). 3448–3448.
5.
Shah, Nirav N., Fateeha Furqan, Anikó Szabó, et al.. (2023). Results from a Phase 1/2 Study of Tandem, Bispecific Anti-CD20/Anti-CD19 (LV20.19) CAR T-Cells for Mantle Cell Lymphoma. Transplantation and Cellular Therapy. 29(2). S33–S34. 1 indexed citations
6.
Albinger, Nawid, Sarah Mertlitz, Hermann Kreyenberg, et al.. (2022). Primary CD33-targeting CAR-NK cells for the treatment of acute myeloid leukemia. Blood Cancer Journal. 12(4). 61–61. 70 indexed citations
7.
Knight, Jennifer M., Anikó Szabó, Sharon Yim, et al.. (2022). Patient-reported outcomes and neurotoxicity markers in patients treated with bispecific LV20.19 CAR T cell therapy. SHILAP Revista de lepidopterología. 2(1). 49–49. 9 indexed citations
8.
Albinger, Nawid, et al.. (2022). Primary CD33-targeting CAR-NK cells for the treatment of acute myeloid leukemia. Klinische Pädiatrie. 234(3). 181–181. 2 indexed citations
9.
Alabanza, Leah, Ying Xiong, Bang K. Vu, et al.. (2022). Armored BCMA CAR T Cells Eliminate Multiple Myeloma and Are Resistant to the Suppressive Effects of TGF-β. Frontiers in Immunology. 13. 832645–832645. 41 indexed citations
10.
Shah, Nirav N., Joanna Zurko, Timothy S. Fenske, et al.. (2021). Clinical and Manufacturing Outcomes of LV20.19 CAR T-Cells Expanded in IL-2 Versus IL-7 and IL-15. Transplantation and Cellular Therapy. 27(3). S194–S195. 1 indexed citations
11.
Krueger, Winfried, André Roy, Wa’el Al Rawashdeh, et al.. (2021). Titratable Pharmacological Regulation of CAR T Cells Using Zinc Finger-Based Transcription Factors. Cancers. 13(19). 4741–4741. 13 indexed citations
12.
Zurko, Joanna, Huiqing Xu, Dina Schneider, et al.. (2021). Manufacturing Bispecific LV20.19 CAR T-Cells with IL-7 & IL-15 for a Shorter Duration Improves CAR T-Cell Immunophenotype While Maintaining Target Cell Dose. Blood. 138(Supplement 1). 3883–3883. 2 indexed citations
13.
Shah, Nirav N., Bryon D. Johnson, Dina Schneider, et al.. (2020). Bispecific anti-CD20, anti-CD19 CAR T cells for relapsed B cell malignancies: a phase 1 dose escalation and expansion trial. Nature Medicine. 26(10). 1569–1575. 318 indexed citations breakdown →
14.
Bari, Rafijul, Markus Granzin, Kam Sze Tsang, et al.. (2019). A Distinct Subset of Highly Proliferative and Lentiviral Vector (LV)-Transducible NK Cells Define a Readily Engineered Subset for Adoptive Cellular Therapy. Frontiers in Immunology. 10. 2001–2001. 72 indexed citations
15.
Schneider, Dina, Ying Xiong, Peirong Hu, et al.. (2018). A Unique Human Immunoglobulin Heavy Chain Variable Domain-Only CD33 CAR for the Treatment of Acute Myeloid Leukemia. Frontiers in Oncology. 8. 539–539. 32 indexed citations
16.
Zhu, Fenlu, Nirav N. Shah, Huiqing Xu, et al.. (2016). CAR-T Cell Production Using the Clinimacs® Prodigy System. Blood. 128(22). 5724–5724. 14 indexed citations
17.
Minici, Claudia, Dina Schneider, Alpaslan Tasdogan, et al.. (2016). Distinct Homotypic B-Cell Receptor Interactions Shape The Outcome Of Chronic Lymphocytic Leukemia. Haematologica. 101. 9–9. 2 indexed citations
18.
Schneider, Dina, Shyamala Ganesan, Adam T. Comstock, et al.. (2010). Increased Cytokine Response of Rhinovirus-infected Airway Epithelial Cells in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 182(3). 332–340. 143 indexed citations
19.
Wang, Qiong, Deepti R. Nagarkar, Emily Bowman, et al.. (2009). Role of Double-Stranded RNA Pattern Recognition Receptors in Rhinovirus-Induced Airway Epithelial Cell Responses. The Journal of Immunology. 183(11). 6989–6997. 199 indexed citations
20.
Schneider, Dina, et al.. (2008). 2,3,7,8-Tetrachlorodibenzo-p-dioxin-Mediated Impairment of B Cell Differentiation Involves Dysregulation of Paired Box 5 (Pax5) Isoform, Pax5a. Journal of Pharmacology and Experimental Therapeutics. 326(2). 463–474. 28 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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