Sascha Dietrich

10.4k total citations · 2 hit papers
158 papers, 4.5k citations indexed

About

Sascha Dietrich is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Sascha Dietrich has authored 158 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 54 papers in Oncology and 48 papers in Genetics. Recurrent topics in Sascha Dietrich's work include Lymphoma Diagnosis and Treatment (43 papers), Chronic Lymphocytic Leukemia Research (37 papers) and CAR-T cell therapy research (23 papers). Sascha Dietrich is often cited by papers focused on Lymphoma Diagnosis and Treatment (43 papers), Chronic Lymphocytic Leukemia Research (37 papers) and CAR-T cell therapy research (23 papers). Sascha Dietrich collaborates with scholars based in Germany, United States and Switzerland. Sascha Dietrich's co-authors include Thorsten Zenz, Wolfgang Huber, Peter Dreger, Anthony D. Ho, Heiko Liesegang, Britta Velten, Florian Buettner, Ricard Argelaguet, John C. Marioni and Damien Arnol and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Sascha Dietrich

140 papers receiving 4.4k citations

Hit Papers

Multi‐Omics Factor Analysis—a framework for unsupervised ... 2018 2026 2020 2023 2018 2022 200 400 600

Peers

Sascha Dietrich
Debashis Sahoo United States
Ken Mills United Kingdom
Adam J. Bass United States
Barbara A. Zehnbauer United States
Dong Shen China
David C. Wedge United Kingdom
Judith M. Boer Netherlands
Stanley Pounds United States
P. Mickey Williams United States
Debashis Sahoo United States
Sascha Dietrich
Citations per year, relative to Sascha Dietrich Sascha Dietrich (= 1×) peers Debashis Sahoo

Countries citing papers authored by Sascha Dietrich

Since Specialization
Citations

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

Fields of papers citing papers by Sascha Dietrich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sascha Dietrich

This figure shows the co-authorship network connecting the top 25 collaborators of Sascha Dietrich. A scholar is included among the top collaborators of Sascha Dietrich 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 Sascha Dietrich. Sascha Dietrich 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.
Lindenhofer, Dominik, Julia Bauman, John A. Hawkins, et al.. (2025). Functional phenotyping of genomic variants using joint multiomic single-cell DNA–RNA sequencing. Nature Methods. 22(10). 2032–2041.
2.
Scharf, Sebastian, Paul Jäger, Guido Kobbe, et al.. (2025). Dynamic Prediction of Mortality Risk Following Allogeneic Hematopoietic Stem Cell Transplantation. SHILAP Revista de lepidopterología.
3.
Werner, Julia, Mitrajit Ghosh, Michał Gorzkiewicz, et al.. (2025). Myoglobin expression improves T-cell metabolism and antitumor effector function. Journal for ImmunoTherapy of Cancer. 13(6). e011503–e011503. 1 indexed citations
4.
Zhou, Meijun, et al.. (2024). Drug‐Induced Differential Gene Expression Analysis on Nanoliter Droplet Microarrays: Enabling Tool for Functional Precision Oncology. Advanced Healthcare Materials. 14(1). e2401820–e2401820. 1 indexed citations
5.
Koch, Annemarie, Roland Fenk, Uwe Maus, et al.. (2024). Stromal alterations in patients with monoclonal gammopathy of undetermined significance, smoldering myeloma, and multiple myeloma. Blood Advances. 8(10). 2575–2588. 4 indexed citations
6.
Pfeuffer, Steffen, Marc Pawlitzki, Tobias Ruck, et al.. (2024). Abatacept Induces Long-Term Reconstitution of the B-Cell Niche in a Patient With CTLA-4 Haploinsufficiency. Neurology Neuroimmunology & Neuroinflammation. 12(2). e200351–e200351.
7.
Roider, Tobias, Norman Mack, Peter‐Martin Bruch, et al.. (2024). CD20-bispecific antibodies improve response to CD19-CAR T cells in lymphoma in vitro and CLL in vivo models. Blood. 144(7). 784–789. 7 indexed citations
8.
Bruch, Peter‐Martin, Christoph Peter, Sanil Bhatia, et al.. (2024). Novel meriolin derivatives potently inhibit cell cycle progression and transcription in leukemia and lymphoma cells via inhibition of cyclin-dependent kinases (CDKs). Cell Death Discovery. 10(1). 279–279. 7 indexed citations
9.
Jäger, Paul, Johanna Tischer, Alessia Fraccaroli, et al.. (2024). Smart Conditioning with Venetoclax-Enhanced Sequential FLAMSA + RIC in Patients with High-Risk Myeloid Malignancies. Cancers. 16(3). 532–532. 6 indexed citations
10.
Herbst, Sophie A., Vladislav Kim, Tobias Roider, et al.. (2023). Comparing the value of mono- vs coculture for high-throughput compound screening in hematological malignancies. Blood Advances. 7(19). 5925–5936. 7 indexed citations
11.
Kaufmann, Stefan, Kentaro Hayashi, Masaki Nakahata, et al.. (2023). Reversible Host–Guest Crosslinks in Supramolecular Hydrogels for On‐Demand Mechanical Stimulation of Human Mesenchymal Stem Cells. Advanced Healthcare Materials. 13(10). e2302607–e2302607. 4 indexed citations
12.
Bruch, Peter‐Martin, Carolin Kolb, Sophie A. Herbst, et al.. (2022). Drug‐microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL. Molecular Systems Biology. 18(8). e10855–e10855. 10 indexed citations
13.
Roessner, Philipp M., Laura Llaó Cid, Tobias Roider, et al.. (2021). EOMES and IL-10 regulate antitumor activity of T regulatory type 1 CD4+ T cells in chronic lymphocytic leukemia. Leukemia. 35(8). 2311–2324. 30 indexed citations
14.
Cid, Laura Llaó, Philipp M. Roessner, Vicente Chapaprieta, et al.. (2021). EOMES is essential for antitumor activity of CD8+ T cells in chronic lymphocytic leukemia. Leukemia. 35(11). 3152–3162. 29 indexed citations
15.
Öztürk, Selcen, Irene Gil-Fariña, Anna Jauch, et al.. (2021). Longitudinal analyses of CLL in mice identify leukemia-related clonal changes including a Myc gain predicting poor outcome in patients. Leukemia. 36(2). 464–475. 6 indexed citations
16.
Genard, Géraldine, S. Öhl, Michelle Neßling, et al.. (2020). Optimized Protocol for Isolation of Small Extracellular Vesicles from Human and Murine Lymphoid Tissues. International Journal of Molecular Sciences. 21(15). 5586–5586. 22 indexed citations
17.
Argelaguet, Ricard, Britta Velten, Damien Arnol, et al.. (2018). Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets. Molecular Systems Biology. 14(6). e8124–e8124. 664 indexed citations breakdown →
18.
Wu, Bian, Mikołaj Słabicki, Leopold Sellner, et al.. (2017). MED12 mutations and NOTCH signalling in chronic lymphocytic leukaemia. British Journal of Haematology. 179(3). 421–429. 27 indexed citations
19.
Sellner, Leopold, Monika Brüggemann, Henrik Knecht, et al.. (2016). GvL effects in T-prolymphocytic leukemia: evidence from MRD kinetics and TCR repertoire analyses. Bone Marrow Transplantation. 52(4). 544–551. 25 indexed citations
20.
Dietrich, Sascha, et al.. (2012). ErP-Directive: Implementation - transposition - verification. 1–5. 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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