Guy Pratt
Impact in
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research
- Genetic Associations and Epidemiology
- Hematology top 0.5%
- Multiple Myeloma Research and Treatments
Papers in
- Hematology 121
- Multiple Myeloma Research and Treatments 106
- Hematopoietic Stem Cell Transplantation 7
- Genetics 82
- Chronic Lymphocytic Leukemia Research 81
- Co-authors
- Paul Moss (43 shared papers)Chris Fegan (37 shared papers)Chris J. Pepper (32 shared papers)Oliver Charles Goodyear (7 shared papers)Gareth John Morgan (26 shared papers)Tatjana Stanković (16 shared papers)Jane Starczynski (15 shared papers)Roger G. Owen (24 shared papers)
- Journals
- British Journal of Haematology (61 papers)Blood (40 papers)Leukemia (12 papers)Haematologica (8 papers)Blood Cancer Journal (7 papers)
- Partner nations
- United KingdomUnited StatesSweden
In The Last Decade
Guy Pratt
235 papers receiving 8.2k citations
Peers
Comparison fields: 5 of 121
- Genetics 1.8k
- Hematology 2.6k
- Oncology 896
- Hepatology 268
- Immunology 532
Countries citing papers authored by Guy Pratt
This map shows the geographic impact of Guy Pratt'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 Guy Pratt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guy Pratt more than expected).
Fields of papers citing papers by Guy Pratt
This network shows the impact of papers produced by Guy Pratt. 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 Guy Pratt. The network helps show where Guy Pratt may publish in the future.
Co-authors
The 25 scholars most cited alongside Guy Pratt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 248 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 304 | |
| 2 | 2007 | 289 | |
| 3 | 2010 | 260 | |
| 4 | 2006 | 254 | |
| 5 | 2011 | 247 | |
| 6 | 2015 | 243 | |
| 7 | 2008 | 201 | |
| 8 | 2010 | 197 | |
| 9 | 2013 | 183 | |
| 10 | 2011 | 169 | |
| 11 | 2013 | 159 | |
| 12 | 2010 | 147 | |
| 13 | 2013 | 146 | |
| 14 | 2008 | 141 | |
| 15 | 2015 | 139 | |
| 16 | 2019 | 132 | |
| 17 | 2012 | 123 | |
| 18 | 2015 | 122 | |
| 19 | 2014 | 121 | |
| 20 | 2016 | 119 |
About Guy Pratt
Guy Pratt is a scholar working on Hematology, Genetics, Immunology, Oncology and Pathology and Forensic Medicine, having authored 248 papers that have together received 8.4k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (106 papers), Chronic Lymphocytic Leukemia Research (81 papers), Hematopoietic Stem Cell Transplantation (7 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (7 papers), Lymphoma Diagnosis and Treatment (7 papers), SARS-CoV-2 and COVID-19 Research (5 papers), T-cell and B-cell Immunology (4 papers) and Cytomegalovirus and herpesvirus research (4 papers). The work is most often cited by research in Genetics (1.8k citations), Hematology (2.6k citations), Oncology (896 citations), Hepatology (268 citations) and Immunology (532 citations). Guy Pratt has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Paul Moss, Chris Fegan, Chris J. Pepper, Oliver Charles Goodyear, Gareth John Morgan, Tatjana Stanković, Jane Starczynski, Roger G. Owen, Helen Parry and Mark Trehane Drayson. Their work appears in journals such as British Journal of Haematology, Blood, Leukemia, Haematologica and Blood Cancer Journal.
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.