Maximilian Merz

1.6k total citations
54 papers, 670 citations indexed

About

Maximilian Merz is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, Maximilian Merz has authored 54 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Hematology, 21 papers in Oncology and 19 papers in Molecular Biology. Recurrent topics in Maximilian Merz's work include Multiple Myeloma Research and Treatments (28 papers), CAR-T cell therapy research (12 papers) and Protein Degradation and Inhibitors (10 papers). Maximilian Merz is often cited by papers focused on Multiple Myeloma Research and Treatments (28 papers), CAR-T cell therapy research (12 papers) and Protein Degradation and Inhibitors (10 papers). Maximilian Merz collaborates with scholars based in Germany, United States and Belgium. Maximilian Merz's co-authors include Tobias Bäuerle, Wolfhard Semmler, Dorde Komljenovic, Jens Hillengaß, Hartmut Goldschmidt, Stefan Zwick, Marc S. Raab, Anna Jauch, K. Martin Kortüm and Simon L. Goodman and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Maximilian Merz

50 papers receiving 658 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maximilian Merz Germany 14 360 324 246 110 66 54 670
John D. Iuliucci United States 13 316 0.9× 122 0.4× 212 0.9× 40 0.4× 45 0.7× 16 637
Allison Theus United States 7 572 1.6× 294 0.9× 195 0.8× 35 0.3× 28 0.4× 8 927
RN Buick Canada 11 381 1.1× 417 1.3× 220 0.9× 44 0.4× 103 1.6× 19 857
Michael A. Damore United States 16 302 0.8× 131 0.4× 276 1.1× 144 1.3× 68 1.0× 30 775
Mingqing Zhu China 11 246 0.7× 278 0.9× 439 1.8× 25 0.2× 66 1.0× 53 809
Sonja Seidl Austria 11 430 1.2× 190 0.6× 113 0.5× 25 0.2× 59 0.9× 25 599
Hua Dong China 10 290 0.8× 228 0.7× 213 0.9× 22 0.2× 256 3.9× 28 691
J. Graham Sharp United States 12 181 0.5× 255 0.8× 250 1.0× 35 0.3× 96 1.5× 26 633

Countries citing papers authored by Maximilian Merz

Since Specialization
Citations

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

Fields of papers citing papers by Maximilian Merz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maximilian Merz

This figure shows the co-authorship network connecting the top 25 collaborators of Maximilian Merz. A scholar is included among the top collaborators of Maximilian Merz 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 Maximilian Merz. Maximilian Merz 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.
Merz, Maximilian, Wolfram Stiller, Stephan Skornitzke, et al.. (2024). Calcium-Based Imaging of the Spine at Dual-Layer CT and Evaluation of Vertebral Fractures in Multiple Myeloma. Cancers. 16(15). 2688–2688. 1 indexed citations
2.
Schwind, Sebastian, Marius Bill, Juliane Grimm, et al.. (2024). Quantifying NPM1 MRD in AML patients prior to allogeneic stem cell transplantation: Where to draw the line?. HemaSphere. 8(3). e55–e55. 2 indexed citations
3.
Kreuz, Markus, et al.. (2024). Predicting Progression Events in Multiple Myeloma from Routine Blood Work. Blood. 144(Supplement 1). 7476–7476.
4.
Sachpekidis, Christos, Olof Enqvist, Johannes Ulén, et al.. (2024). Artificial intelligence–based, volumetric assessment of the bone marrow metabolic activity in [18F]FDG PET/CT predicts survival in multiple myeloma. European Journal of Nuclear Medicine and Molecular Imaging. 51(8). 2293–2307. 8 indexed citations
5.
6.
Schmiedel, Dominik, Andreas Boldt, Vladan Vučinić, et al.. (2024). Evaluation of Anti-CAR Linker mAbs for CAR T Monitoring after BiTEs/bsAbs and CAR T-Cell Pretreatment. Biomedicines. 12(8). 1641–1641. 2 indexed citations
7.
Fischer, Luise, et al.. (2023). CAR T cell therapy in multiple myeloma, where are we now and where are we heading for?. European Journal Of Haematology. 112(1). 19–27. 3 indexed citations
8.
Špıčka, Ivan, Maximilian Merz, Jakub Radocha, et al.. (2023). P944: REAL-WORLD PATIENT CHARACTERISTICS AND SURVIVAL OUTCOMES OF LENALIDOMIDE REFRACTORY VS. LENALIDOMIDE EXPOSED RRMM PATIENTS IN THE HONEUR FEDERATED DATA NETWORK. HemaSphere. 7(S3). e258126d–e258126d. 2 indexed citations
9.
Friedrich, Maik, Maximilian Merz, Vladan Vučinić, et al.. (2023). Teclistamab impairs detection of BCMA CAR-T cells. Blood Advances. 7(15). 3842–3845. 4 indexed citations
10.
Georgi, Thomas, Lars Kurch, Georg‐Nikolaus Franke, et al.. (2023). Prognostic value of baseline and early response FDG-PET/CT in patients with refractory and relapsed aggressive B-cell lymphoma undergoing CAR-T cell therapy. Journal of Cancer Research and Clinical Oncology. 149(9). 6131–6138. 11 indexed citations
11.
Neuhaus, Vanessa, Dennis Löffler, Conny Blumert, et al.. (2023). A time-resolved meta-analysis of consensus gene expression profiles during human T-cell activation. Genome biology. 24(1). 287–287. 8 indexed citations
12.
Jentzsch, Madlen, Klaus H. Metzeler, Maximilian Merz, et al.. (2022). Prognostic impact of the AML ELN2022 risk classification in patients undergoing allogeneic stem cell transplantation. Blood Cancer Journal. 12(12). 170–170. 20 indexed citations
13.
Kubasch, Anne Sophie, et al.. (2021). Predicting Early Relapse for Patients with Multiple Myeloma through Machine Learning. Blood. 138(Supplement 1). 2953–2953. 4 indexed citations
14.
Berkholz, Christoph & Maximilian Merz. (2021). Probabilistic Databases under Updates. 402–415. 1 indexed citations
15.
Merz, Maximilian, Yali Zhang, George L. Chen, et al.. (2020). Serological Response to Vaccination after Autologous Transplantation for Multiple Myeloma Is Associated with Improved Progression-Free and Overall Survival. Transplantation and Cellular Therapy. 27(3). 245.e1–245.e8. 3 indexed citations
16.
17.
Merz, Maximilian, Anna Jauch, Thomas Hielscher, et al.. (2017). Prognostic significance of cytogenetic heterogeneity in patients with newly diagnosed multiple myeloma. Blood Advances. 2(1). 1–9. 22 indexed citations
18.
Merz, Maximilian, et al.. (2014). Assessing Treatment Response of Osteolytic Lesions by Manual Volumetry, Automatic Segmentation, and RECIST in Experimental Bone Metastases. Academic Radiology. 21(9). 1177–1184. 6 indexed citations
19.
Bäuerle, Tobias, Dorde Komljenovic, Maximilian Merz, et al.. (2010). Cilengitide inhibits progression of experimental breast cancer bone metastases as imaged noninvasively using VCT, MRI and DCE‐MRI in a longitudinal in vivo study. International Journal of Cancer. 128(10). 2453–2462. 65 indexed citations
20.
Bäuerle, Tobias, Maximilian Merz, Dorde Komljenovic, Stefan Zwick, & Wolfhard Semmler. (2010). Drug-Induced Vessel Remodeling in Bone Metastases as Assessed by Dynamic Contrast Enhanced Magnetic Resonance Imaging and Vessel Size Imaging: A LongitudinalIn vivoStudy. Clinical Cancer Research. 16(12). 3215–3225. 39 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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