Thomas McKerrell
Impact in
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
- Chronic Myeloid Leukemia Treatments
- Genetics top 5%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Hemoglobinopathies and Related Disorders
Papers in ⓘ
-
- Acute Myeloid Leukemia Research 5
- Multiple Myeloma Research and Treatments 2
- Hematopoietic Stem Cell Transplantation 1
- Genetics 6
- Myeloproliferative Neoplasms: Diagnosis and Treatment 5
- Hemoglobinopathies and Related Disorders 1
- Co-authors
- George S. Vassiliou (5 shared papers)Naomi Park (3 shared papers)Ignacio Varela (3 shared papers)Hannes Ponstingl (2 shared papers)Thaidy Moreno-Rodriguez (2 shared papers)Roland Rad (2 shared papers)Charles Crawley (2 shared papers)Carolyn Grove (2 shared papers)
- Journals
- Blood (2 papers)Science Translational Medicine (1 paper)Blood Advances (1 paper)Haematologica (1 paper)American Journal of Hematology (1 paper)
- Partner nations
- United KingdomSpainGermany
In The Last Decade
Thomas McKerrell
8 papers receiving 528 citations
Hit Papers
Peers
Comparison fields: 5 of 45
- Hematology 417
- Genetics 270
- Cancer Research 135
- Molecular Biology 228
- Aging 5
Countries citing papers authored by Thomas McKerrell
This map shows the geographic impact of Thomas McKerrell'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 Thomas McKerrell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas McKerrell more than expected).
Fields of papers citing papers by Thomas McKerrell
This network shows the impact of papers produced by Thomas McKerrell. 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 Thomas McKerrell. The network helps show where Thomas McKerrell may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas McKerrell, 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 | Leukemia-Associated Somatic Mutations Drive Distinct Patterns of Age-Related Clonal Hemopoiesis Hit paper breakdown → | 2015 | 357 |
| 2 | 2017 | 38 | |
| 3 | 2014 | 37 | |
| 4 | 2015 | 32 | |
| 5 | 2019 | 28 | |
| 6 | 2004 | 24 | |
| 7 | 2012 | 12 | |
| 8 | 2018 | 4 |
About Thomas McKerrell
Thomas McKerrell is a scholar working on Hematology, Genetics, Cancer Research, Molecular Biology and Speech and Hearing, having authored 8 papers that have together received 532 indexed citations. Recurring topics across this work include Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), Acute Myeloid Leukemia Research (5 papers), Cancer Genomics and Diagnostics (3 papers), Multiple Myeloma Research and Treatments (2 papers), Adolescent and Pediatric Healthcare (1 paper), Kruppel-like factors research (1 paper), Hemoglobinopathies and Related Disorders (1 paper) and Hematopoietic Stem Cell Transplantation (1 paper). The work is most often cited by research in Hematology (417 citations), Genetics (270 citations), Cancer Research (135 citations), Molecular Biology (228 citations) and Aging (5 citations). Thomas McKerrell has collaborated with scholars based in United Kingdom, Spain and Germany. Frequent co-authors include George S. Vassiliou, Naomi Park, Ignacio Varela, Hannes Ponstingl, Thaidy Moreno-Rodriguez, Roland Rad, Charles Crawley, Carolyn Grove, Michael A. Quail and Eleftheria Zeggini. Their work appears in journals such as Blood, Science Translational Medicine, Blood Advances, Haematologica and American Journal of Hematology.
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.