Ingo Roeder

4.4k total citations
109 papers, 2.8k citations indexed

About

Ingo Roeder is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Ingo Roeder has authored 109 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 41 papers in Hematology and 22 papers in Genetics. Recurrent topics in Ingo Roeder's work include Hematopoietic Stem Cell Transplantation (20 papers), Pluripotent Stem Cells Research (17 papers) and Chronic Myeloid Leukemia Treatments (17 papers). Ingo Roeder is often cited by papers focused on Hematopoietic Stem Cell Transplantation (20 papers), Pluripotent Stem Cells Research (17 papers) and Chronic Myeloid Leukemia Treatments (17 papers). Ingo Roeder collaborates with scholars based in Germany, United States and United Kingdom. Ingo Roeder's co-authors include Markus Loeffler, Ingmar Glauche, Matthias Horn, Maria Herberg, Gerd Kempermann, Alexander Garthe, Andreas Hochhaus, Martin Mueller, Nico Scherf and Lars Thielecke and has published in prestigious journals such as Nucleic Acids Research, Nature Medicine and Nature Communications.

In The Last Decade

Ingo Roeder

105 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ingo Roeder Germany	30	1.3k	832	502	390	327	109	2.8k
Ben D. MacArthur United Kingdom	23	2.0k 1.6×	1.4k 1.7×	1.4k 2.7×	681 1.7×	780 2.4×	70	4.9k
Caleb Weinreb United States	17	2.3k 1.8×	523 0.6×	144 0.3×	150 0.4×	641 2.0×	25	3.3k
Guoji Guo China	34	4.0k 3.1×	469 0.6×	265 0.5×	460 1.2×	779 2.4×	67	5.3k
Jessica C. Mar United States	28	1.7k 1.3×	822 1.0×	397 0.8×	511 1.3×	656 2.0×	60	3.2k
Konstantinos D. Kokkaliaris Switzerland	23	990 0.8×	883 1.1×	454 0.9×	415 1.1×	658 2.0×	36	2.3k
David G. Kent United Kingdom	32	2.8k 2.2×	2.3k 2.8×	902 1.8×	489 1.3×	1.5k 4.5×	83	5.3k
Samuel L. Wolock United States	10	2.4k 1.9×	538 0.6×	224 0.4×	383 1.0×	935 2.9×	15	3.5k
Iñigo Martincorena United Kingdom	26	3.5k 2.7×	461 0.6×	276 0.5×	1.2k 3.1×	462 1.4×	45	6.3k
Antonio Scialdone Italy	25	3.5k 2.8×	222 0.3×	235 0.5×	382 1.0×	546 1.7×	82	5.2k
Anna Marciniak‐Czochra Germany	29	870 0.7×	369 0.4×	216 0.4×	341 0.9×	144 0.4×	105	2.4k

Countries citing papers authored by Ingo Roeder

Since Specialization

Citations

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

Fields of papers citing papers by Ingo Roeder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ingo Roeder

This figure shows the co-authorship network connecting the top 25 collaborators of Ingo Roeder. A scholar is included among the top collaborators of Ingo Roeder 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 Ingo Roeder. Ingo Roeder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yong, Agnes S. M., et al.. (2025). Predicting treatment-free remission in chronic myeloid leukemia patients using an integrated model of tumor-immune dynamics. npj Systems Biology and Applications. 11(1). 115–115.

Sidorova, Olga Alexandra, Maciej Paszkowski‐Rogacz, Michael Seifert, et al.. (2022). RNAi-Mediated Screen of Primary AML Cells Nominates MDM4 as a Therapeutic Target in NK-AML with DNMT3A Mutations. Cells. 11(5). 854–854. 5 indexed citations

Herling, Marco, et al.. (2022). Computational gene expression analysis reveals distinct molecular subgroups of T-cell prolymphocytic leukemia. PLoS ONE. 17(9). e0274463–e0274463. 3 indexed citations

Roeder, Ingo, et al.. (2022). Comparative Gene Expression Analysis Reveals Similarities and Differences of Chronic Myeloid Leukemia Phases. Cancers. 14(1). 256–256. 5 indexed citations

Thiede, Christian, et al.. (2020). Differential response to cytotoxic therapy explains treatment dynamics of acute myeloid leukaemia patients: insights from a mathematical modelling approach. Journal of The Royal Society Interface. 17(170). 20200091–20200091. 9 indexed citations

Johansson, Patricia, Ludger Klein‐Hitpaß, Bettina Budeus, et al.. (2020). Identifying Genetic Lesions in Ocular Adnexal Extranodal Marginal Zone Lymphomas of the MALT Subtype by Whole Genome, Whole Exome and Targeted Sequencing. Cancers. 12(4). 986–986. 17 indexed citations

Lauber, Chris, Nádia Correia, Andreas Trumpp, et al.. (2020). Survival differences and associated molecular signatures of DNMT3A-mutant acute myeloid leukemia patients. Scientific Reports. 10(1). 12761–12761. 19 indexed citations

Roeder, Ingo & Ingmar Glauche. (2020). Overlooking the obvious? On the potential of treatment alterations to predict patient-specific therapy response. Experimental Hematology. 94. 26–30. 4 indexed citations

Zakrzewski, Falk, Walter de Back, Martin Weigert, et al.. (2019). Automated detection of the HER2 gene amplification status in Fluorescence in situ hybridization images for the diagnostics of cancer tissues. Scientific Reports. 9(1). 8231–8231. 37 indexed citations

10.

Franke, Annika, et al.. (2018). Paracrine mechanisms in early differentiation of human pluripotent stem cells: Insights from a mathematical model. Stem Cell Research. 32. 1–7. 12 indexed citations

11.

Diebner, Hans H., et al.. (2018). Metabolism is the tie: The Bertalanffy-type cancer growth model as common denominator of various modelling approaches. Biosystems. 167. 1–23. 5 indexed citations

12.

Hohenstein, Bernd, Ulrich Julius, Peter Lansberg, et al.. (2017). Rationale and design of MultiSELECt: A European Multi center S tudy on the E ffect of L ipoprotein(a) E limination by lipoprotein apheresis on C ardiovascular ou t comes. Atherosclerosis Supplements. 30. 180–186. 23 indexed citations

13.

Gerbaulet, Alexander, Thomas Zerjatke, Ingo Roeder, et al.. (2017). The bulk of the hematopoietic stem cell population is dispensable for murine steady-state and stress hematopoiesis. Experimental Hematology. 53. S105–S105. 2 indexed citations

14.

Thielecke, Lars, Andreas Dahl, Rajiv Lochan Tiwari, et al.. (2017). Limitations and challenges of genetic barcode quantification. Scientific Reports. 7(1). 43249–43249. 34 indexed citations

15.

Shah, Gopi, et al.. (2016). Biology-inspired visualization of morphogenetic motion in the zebrafish endoderm. 126. 925–929. 1 indexed citations

16.

Becker, Tim, et al.. (2014). The benchmark data SET CeTReS.B-MI for in vitro mitosis detection. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 504. 469–472.

17.

Rashidi, Narges, Mark Scott, Nico Scherf, et al.. (2014). In vivo time-lapse imaging shows diverse niche engagement by quiescent and naturally activated hematopoietic stem cells. Blood. 124(1). 79–83. 48 indexed citations

18.

Giordano, Frank A., Ursula R. Sorg, Nico Lachmann, et al.. (2011). Clonal Inventory Screens Uncover Monoclonality Following Serial Transplantation of MGMT ^P140K -Transduced Stem Cells and Dose-Intense Chemotherapy. Human Gene Therapy. 22(6). 697–710. 14 indexed citations

19.

Roeder, Ingo, Markus Loeffler, & Ingmar Glauche. (2011). Towards a quantitative understanding of stem cell–niche interaction: Experiments, models, and technologies. Blood Cells Molecules and Diseases. 46(4). 308–317. 27 indexed citations

20.

Dette, Holger & Ingo Roeder. (2000). Online Calculation of Efficient Designs for Multi-Factor Models. Biometrical Journal. 42(3). 349–362. 3 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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