Tim Grob
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
- Genetics top 10%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
Papers in
- Hematology 18
- Acute Myeloid Leukemia Research 17
- Chronic Myeloid Leukemia Treatments 3
- Multiple Myeloma Research and Treatments 2
-
- Protein Degradation and Inhibitors 7
- Histone Deacetylase Inhibitors Research 5
- Co-authors
- Peter J.M. Valk (14 shared papers)Mojca Jongen‐Lavrencic (8 shared papers)Bob Löwenberg (11 shared papers)Gert J. Ossenkoppele (8 shared papers)Melissa Rijken (8 shared papers)Mathijs A. Sanders (7 shared papers)Patrycja Gradowska (4 shared papers)Marinus van Marwijk Kooy (4 shared papers)
- Journals
- Blood (5 papers)Blood Advances (3 papers)Molecular Oncology (2 papers)HemaSphere (1 paper)Journal of Clinical Oncology (1 paper)
- Partner nations
- NetherlandsSwitzerlandBelgium
In The Last Decade
Tim Grob
17 papers receiving 421 citations
Tim Grob's Hit Papers
Peers
Comparison fields: 5 of 53
- Hematology 309
- Genetics 98
- Cancer Research 52
- Molecular Biology 190
- Neurology 20
Countries citing papers authored by Tim Grob
This map shows the geographic impact of Tim Grob'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 Tim Grob with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Grob more than expected).
Fields of papers citing papers by Tim Grob
This network shows the impact of papers produced by Tim Grob. 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 Tim Grob. The network helps show where Tim Grob may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Grob, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Molecular characterization of mutant TP53 acute myeloid leukemia and high-risk myelodysplastic syndrome Hit paper breakdown → | 2022 | 159 |
| 2 | 2013 | 69 | |
| 3 | 2022 | 69 | |
| 4 | 2020 | 44 | |
| 5 | 2021 | 29 | |
| 6 | 2020 | 22 | |
| 7 | 2021 | 7 | |
| 8 | 2021 | 6 | |
| 9 | 2021 | 6 | |
| 10 | 2017 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2022 | 1 | |
| 15 | 2018 | 1 | |
| 16 | 2016 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2025 | 0 |
About Tim Grob
Tim Grob is a scholar working on Hematology, Molecular Biology, Genetics, Cancer Research and Pulmonary and Respiratory Medicine, having authored 18 papers that have together received 423 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (17 papers), Protein Degradation and Inhibitors (7 papers), Histone Deacetylase Inhibitors Research (5 papers), Cancer Genomics and Diagnostics (3 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), Chronic Myeloid Leukemia Treatments (3 papers), Sarcoma Diagnosis and Treatment (3 papers) and Multiple Myeloma Research and Treatments (2 papers). The work is most often cited by research in Hematology (309 citations), Genetics (98 citations), Cancer Research (52 citations), Molecular Biology (190 citations) and Neurology (20 citations). Tim Grob has collaborated with scholars based in Netherlands, Switzerland and Belgium. Frequent co-authors include Peter J.M. Valk, Mojca Jongen‐Lavrencic, Bob Löwenberg, Gert J. Ossenkoppele, Melissa Rijken, Mathijs A. Sanders, Patrycja Gradowska, Marinus van Marwijk Kooy, H. Berna Beverloo and François G. Kavelaars. Their work appears in journals such as Blood, Blood Advances, Molecular Oncology, HemaSphere and Journal of Clinical Oncology.
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.