Karl Eckert
Impact in
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research
- Virus-based gene therapy research
- Developmental Neuroscience top 5%
- Neurogenesis and neuroplasticity mechanisms
Papers in
- Genetics 14
- Chronic Lymphocytic Leukemia Research 14
-
- Lymphoma Diagnosis and Treatment 7
- Cancer Mechanisms and Therapy 2
- Co-authors
- Nobuko Uchida (1 shared paper)Sunil Jain (1 shared paper)Brent T. Harris (1 shared paper)Fred H. Gage (1 shared paper)Robert Tushinski (1 shared paper)Richard E. Sutton (1 shared paper)Irving L. Weissman (1 shared paper)Stanley Tamaki (1 shared paper)
- Journals
- Blood (4 papers)British Journal of Haematology (2 papers)Journal of Clinical Oncology (2 papers)Molecular Cancer Therapeutics (1 paper)Clinical Cancer Research (1 paper)
- Partner nations
- United StatesAustraliaBelgium
In The Last Decade
Karl Eckert
19 papers receiving 576 citations
Peers
Comparison fields: 5 of 65
- Genetics 307
- Developmental Neuroscience 101
- Pathology and Forensic Medicine 280
- Hematology 70
- Oncology 149
Countries citing papers authored by Karl Eckert
This map shows the geographic impact of Karl Eckert'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 Karl Eckert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Eckert more than expected).
Fields of papers citing papers by Karl Eckert
This network shows the impact of papers produced by Karl Eckert. 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 Karl Eckert. The network helps show where Karl Eckert may publish in the future.
Co-authors
The 25 scholars most cited alongside Karl Eckert, 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 | 2002 | 186 | |
| 2 | 2001 | 59 | |
| 3 | 2017 | 45 | |
| 4 | 2015 | 39 | |
| 5 | 2021 | 39 | |
| 6 | The role of PIM1 in the ibrutinib-resistant ABC subtype of diffuse large B-cell lymphoma. | 2016 | 37 |
| 7 | 2018 | 32 | |
| 8 | 2019 | 31 | |
| 9 | 2013 | 30 | |
| 10 | 2020 | 20 | |
| 11 | 2023 | 20 | |
| 12 | 2018 | 20 | |
| 13 | 2014 | 7 | |
| 14 | 2022 | 6 | |
| 15 | 2020 | 5 | |
| 16 | 2022 | 2 | |
| 17 | 2020 | 1 | |
| 18 | 2017 | 1 | |
| 19 | 2009 | 1 |
About Karl Eckert
Karl Eckert is a scholar working on Genetics, Pathology and Forensic Medicine, Immunology, Hematology and Molecular Biology, having authored 19 papers that have together received 581 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (14 papers), Lymphoma Diagnosis and Treatment (7 papers), Chronic Myeloid Leukemia Treatments (3 papers), Immunodeficiency and Autoimmune Disorders (3 papers), Galectins and Cancer Biology (2 papers), Viral-associated cancers and disorders (2 papers), Acute Lymphoblastic Leukemia research (2 papers) and Cancer Mechanisms and Therapy (2 papers). The work is most often cited by research in Genetics (307 citations), Developmental Neuroscience (101 citations), Pathology and Forensic Medicine (280 citations), Hematology (70 citations) and Oncology (149 citations). Karl Eckert has collaborated with scholars based in United States, Australia and Belgium. Frequent co-authors include Nobuko Uchida, Sunil Jain, Brent T. Harris, Fred H. Gage, Robert Tushinski, Richard E. Sutton, Irving L. Weissman, Stanley Tamaki, Michael J. Reitsma and Ann Tsukamoto. Their work appears in journals such as Blood, British Journal of Haematology, Journal of Clinical Oncology, Molecular Cancer Therapeutics and Clinical Cancer Research.
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.