Guido Kobbe

12.3k total citations
204 papers, 5.2k citations indexed

About

Guido Kobbe is a scholar working on Hematology, Genetics and Oncology. According to data from OpenAlex, Guido Kobbe has authored 204 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 164 papers in Hematology, 55 papers in Genetics and 53 papers in Oncology. Recurrent topics in Guido Kobbe's work include Acute Myeloid Leukemia Research (107 papers), Hematopoietic Stem Cell Transplantation (85 papers) and Multiple Myeloma Research and Treatments (39 papers). Guido Kobbe is often cited by papers focused on Acute Myeloid Leukemia Research (107 papers), Hematopoietic Stem Cell Transplantation (85 papers) and Multiple Myeloma Research and Treatments (39 papers). Guido Kobbe collaborates with scholars based in Germany, United States and Netherlands. Guido Kobbe's co-authors include Rainer Haas, Roland Fenk, Thomas Schroeder, Ingmar Bruns, Ulrich Germing, Ulrich Germing, Nicolaus Kröger, Christina Rautenberg, Akos Czibere and Ralf Kronenwett and has published in prestigious journals such as Nature Genetics, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Guido Kobbe

187 papers receiving 5.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guido Kobbe Germany 40 3.8k 1.3k 1.3k 1.1k 1.0k 204 5.2k
Uday Popat United States 43 4.0k 1.1× 1.5k 1.2× 1.9k 1.5× 1.3k 1.2× 936 0.9× 396 6.6k
Ghulam Mufti United Kingdom 27 4.7k 1.3× 2.0k 1.5× 818 0.6× 1.2k 1.1× 790 0.8× 101 5.8k
Nicolas Boissel France 42 3.6k 1.0× 1.2k 0.9× 1.5k 1.1× 2.0k 1.8× 1.9k 1.9× 200 6.1k
Yang O. Huh United States 35 2.4k 0.6× 1.6k 1.2× 1.2k 0.9× 664 0.6× 1.2k 1.1× 104 4.7k
Sherry Pierce United States 36 3.5k 0.9× 1.3k 1.0× 897 0.7× 1.8k 1.6× 971 0.9× 131 4.5k
Jean‐Michel Cayuela France 33 2.1k 0.6× 837 0.6× 784 0.6× 1.0k 0.9× 1.4k 1.3× 101 3.8k
Diane C. Arthur United States 33 2.0k 0.5× 1.1k 0.8× 858 0.6× 1.0k 0.9× 945 0.9× 78 4.1k
Petra Muus Netherlands 37 3.3k 0.9× 1.4k 1.0× 649 0.5× 1.2k 1.0× 808 0.8× 176 5.8k
Sally Arai United States 35 2.4k 0.6× 548 0.4× 1.2k 0.9× 1.1k 1.0× 505 0.5× 149 4.4k
Attilio Olivieri Italy 33 2.2k 0.6× 680 0.5× 1.1k 0.8× 568 0.5× 385 0.4× 156 3.6k

Countries citing papers authored by Guido Kobbe

Since Specialization
Citations

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

Fields of papers citing papers by Guido Kobbe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guido Kobbe

This figure shows the co-authorship network connecting the top 25 collaborators of Guido Kobbe. A scholar is included among the top collaborators of Guido Kobbe 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 Guido Kobbe. Guido Kobbe 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.
Kobbe, Guido, Tobias A.W. Holderried, Martina Crysandt, et al.. (2025). Characteristics of infections after BCMA-directed CAR T-cell therapy for multiple myeloma: a real-world analysis. Blood Advances. 9(6). 1370–1375. 2 indexed citations
3.
Scharf, Sebastian, Paul Jäger, Guido Kobbe, et al.. (2025). Dynamic Prediction of Mortality Risk Following Allogeneic Hematopoietic Stem Cell Transplantation. SHILAP Revista de lepidopterología.
4.
Kündgen, Andrea, Kathrin Nachtkamp, Paul Jäger, et al.. (2025). Outcomes in patients with acute myeloid leukemia older than 70 years within the last 30 years, a single center experience. Annals of Hematology. 104(1). 231–239.
5.
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
7.
Wagner-Drouet, Eva, Daniel Teschner, Christine Wolschke, et al.. (2021). Comparison of Cytomegalovirus-Specific Immune Cell Response to Proteins versus Peptides Using an IFN-γ ELISpot Assay after Hematopoietic Stem Cell Transplantation. Diagnostics. 11(2). 312–312. 1 indexed citations
8.
Rautenberg, Christina, Michael Lauseker, Jennifer Kaivers, et al.. (2021). Prognostic impact of pretransplant measurable residual disease assessed by peripheral blood WT1‐mRNA expression in patients with AML and MDS. European Journal Of Haematology. 107(2). 283–292. 15 indexed citations
9.
Fenk, Roland, Aristoteles Giagounidis, Hartmut Goldschmidt, et al.. (2020). Efficacy and Tolerability of High- versus Low-dose Lenalidomide Maintenance Therapy of Multiple Myeloma after Autologous Blood Stem Cell Transplantation. Clinical Cancer Research. 26(22). 5879–5886. 4 indexed citations
10.
Germing, Ulrich, Thomas Schroeder, Jennifer Kaivers, et al.. (2019). Novel therapies in low- and high-risk myelodysplastic syndrome. Expert Review of Hematology. 12(10). 893–908. 14 indexed citations
11.
Schroeder, Thomas, Michael Lauseker, Christina Rautenberg, et al.. (2019). Comparison between Upfront Transplantation and different Pretransplant Cytoreductive Treatment Approaches in Patients with High-Risk Myelodysplastic Syndrome and Secondary Acute Myelogenous Leukemia. Biology of Blood and Marrow Transplantation. 25(8). 1550–1559. 43 indexed citations
12.
Geyh, Stefanie, Manuel Rodríguez‐Paredes, Paul Jäger, et al.. (2018). Transforming growth factor β1-mediated functional inhibition of mesenchymal stromal cells in myelodysplastic syndromes and acute myeloid leukemia. Haematologica. 103(9). 1462–1471. 47 indexed citations
14.
Neukirchen, Judith, Kathrin Nachtkamp, Carlo Aul, et al.. (2015). Change of prognosis of patients with myelodysplastic syndromes during the last 30 years. Leukemia Research. 39(7). 679–683. 11 indexed citations
15.
Alchalby, Haefaa, Tatjana Zabelina, Guido Kobbe, et al.. (2012). Risk models predicting survival after reduced‐intensity transplantation for myelofibrosis. British Journal of Haematology. 157(1). 75–85. 57 indexed citations
17.
Czibere, Akos, Wolf Christian Prall, Luiz F. Zerbini, et al.. (2006). Exisulind induces apoptosis in advanced myelodysplastic syndrome (MDS) and acute myeloid leukaemia/MDS. British Journal of Haematology. 135(3). 355–357. 11 indexed citations
18.
Knipp, Sabine, Barbara Hildebrandt, Aristoteles Giagounidis, et al.. (2004). Intensive Chemotherapy Is Not Recommended for Patients with AML or High-Risk MDS Aged over 60 Years with Complex Karyotype Anomalies.. Blood. 104(11). 72–72. 6 indexed citations
19.
Steidl, Ulrich, Roland Fenk, Ingmar Bruns, et al.. (2004). Successful transplantation of peripheral blood stem cells mobilized by chemotherapy and a single dose of pegylated G-CSF in patients with multiple myeloma. Bone Marrow Transplantation. 35(1). 33–36. 68 indexed citations
20.
Heyll, A., D. Söhngen, Guido Kobbe, et al.. (1997). Idarubicin, melphalan and cyclophosphamide: an intensified high-dose regimen for the treatment of myeloma patients.. PubMed. 11 Suppl 5. S32–4. 7 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026