Michael Tees

1.1k citations
50 papers · 715 · h-index 13

Impact in

  • Oncology top 10%
    • CAR-T cell therapy research
  • Genetics top 10%
    • Chronic Lymphocytic Leukemia Research
    • Virus-based gene therapy research

Papers in

Michael Tees

46 papers receiving 689 citations

Peers

Michael Tees
Comparison fields: 5 of 66
  • Oncology 282
  • Genetics 109
  • Pathology and Forensic Medicine 136
  • Hematology 63
  • Nutrition and Dietetics 75
Replace J. Stratigos with:
J. Stratigos Greece
Nitya Jain United States
Abdolfattah Sarrafnejad Iran
E. O. Ukaejiofo United Kingdom
Neal Smith United States
Manuel Branco Ferreira Portugal
Atsuo Maemoto Japan
Yiwei Ling Japan
Zhuo Lü China
Ian Storie United Kingdom
Michael Tees relative to J. Stratigos Greece J. Stratigos's profile →
Citations per field
00.5×10×15×18.7×
J. Stratigos · 1×
Citations per year

Countries citing papers authored by Michael Tees

Since Specialization
Citations

This map shows the geographic impact of Michael Tees'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 Michael Tees with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Tees more than expected).

Fields of papers citing papers by Michael Tees

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Tees. 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 Michael Tees. The network helps show where Michael Tees may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Tees, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Tees Line = papers co-authored together Michael Tees links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009225
2 200961
3 202038
4 202137
5 202336
6 202134
7 202232
8 201225
9 202122
10 202517
11 202315
12 202115
13 202214
14 202112
15 202311
16
Abstract 3272: Effect of Non-Soy Legume Consumption on Cholesterol Levels: A Meta-Analysis of Randomized Controlled Trials
200810
17 20239
18 20249
19 20169
20 20238

About Michael Tees

Michael Tees is a scholar working on Oncology, Pathology and Forensic Medicine, Genetics, Immunology and Hematology, having authored 50 papers that have together received 715 indexed citations. Recurring topics across this work include CAR-T cell therapy research (31 papers), Lymphoma Diagnosis and Treatment (17 papers), Chronic Lymphocytic Leukemia Research (15 papers), Biosimilars and Bioanalytical Methods (10 papers), Chronic Myeloid Leukemia Treatments (5 papers), Acute Lymphoblastic Leukemia research (3 papers), Protein Degradation and Inhibitors (2 papers) and Hematopoietic Stem Cell Transplantation (2 papers). The work is most often cited by research in Oncology (282 citations), Genetics (109 citations), Pathology and Forensic Medicine (136 citations), Hematology (63 citations) and Nutrition and Dietetics (75 citations). Michael Tees has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Lydia Bazzano, Donna M. Winham, Angela M. Thompson, Catherine Nguyen, Ian W. Flinn, Frederick L. Locke, Sattva S. Neelapu, David B. Miklos, Xu Xiong and Emily W. Harville. Their work appears in journals such as Journal of Clinical Oncology, Blood, HemaSphere, Transplantation and Cellular Therapy and Hematological 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.

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