Wayne Tam
Impact in
- Cancer Research top 0.5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Genetics top 1%
- Chronic Lymphocytic Leukemia Research
Papers in
-
- Lymphoma Diagnosis and Treatment 52
- Genetics 34
- Chronic Lymphocytic Leukemia Research 22
- Myeloproliferative Neoplasms: Diagnosis and Treatment 12
- Co-authors
- James E. Dahlberg (3 shared papers)Amy Chadburn (18 shared papers)Mario Gómez (8 shared papers)Zongdong Li (1 shared paper)Elsebet Lund (1 shared paper)Peggy S. Eis (1 shared paper)Liping Sun (1 shared paper)William S. Hayward (2 shared papers)
- Journals
- Blood (23 papers)American Journal of Clinical Pathology (9 papers)Modern Pathology (7 papers)Haematologica (4 papers)Leukemia (4 papers)
- Partner nations
- United StatesItalySingapore
In The Last Decade
Wayne Tam
112 papers receiving 5.8k citations
Wayne Tam's Hit Papers
Peers
Comparison fields: 5 of 114
- Cancer Research 2.4k
- Genetics 840
- Pathology and Forensic Medicine 1.3k
- Oncology 1.3k
- Hematology 564
Countries citing papers authored by Wayne Tam
This map shows the geographic impact of Wayne Tam'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 Wayne Tam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wayne Tam more than expected).
Fields of papers citing papers by Wayne Tam
This network shows the impact of papers produced by Wayne Tam. 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 Wayne Tam. The network helps show where Wayne Tam may publish in the future.
Co-authors
The 25 scholars most cited alongside Wayne Tam, 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 116 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Accumulation of miR-155 and BIC RNA in human B cell lymphomas Hit paper breakdown → | 2005 | 1147 |
| 2 | 2005 | 293 | |
| 3 | 2010 | 291 | |
| 4 | 1997 | 253 | |
| 5 | 2014 | 244 | |
| 6 | 2001 | 221 | |
| 7 | 2007 | 190 | |
| 8 | 2014 | 181 | |
| 9 | 2006 | 180 | |
| 10 | 2018 | 173 | |
| 11 | 2010 | 149 | |
| 12 | 2008 | 138 | |
| 13 | 2002 | 128 | |
| 14 | 2011 | 128 | |
| 15 | 2015 | 99 | |
| 16 | 2005 | 97 | |
| 17 | 2016 | 92 | |
| 18 | 2011 | 90 | |
| 19 | 2009 | 89 | |
| 20 | 2018 | 87 |
About Wayne Tam
Wayne Tam is a scholar working on Pathology and Forensic Medicine, Genetics, Hematology, Cancer Research and Oncology, having authored 116 papers that have together received 5.9k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (52 papers), Chronic Lymphocytic Leukemia Research (22 papers), Acute Myeloid Leukemia Research (20 papers), Viral-associated cancers and disorders (15 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (12 papers), Cancer-related molecular mechanisms research (9 papers), Histiocytic Disorders and Treatments (8 papers) and Eosinophilic Disorders and Syndromes (8 papers). The work is most often cited by research in Cancer Research (2.4k citations), Genetics (840 citations), Pathology and Forensic Medicine (1.3k citations), Oncology (1.3k citations) and Hematology (564 citations). Wayne Tam has collaborated with scholars based in United States, Italy and Singapore. Frequent co-authors include James E. Dahlberg, Amy Chadburn, Mario Gómez, Zongdong Li, Elsebet Lund, Peggy S. Eis, Liping Sun, William S. Hayward, Dina Ben‐Yehuda and Daniel M. Knowles. Their work appears in journals such as Blood, American Journal of Clinical Pathology, Modern Pathology, Haematologica and Leukemia.
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.