Michael Man
Impact in
- Oncology top 10%
- Pancreatic and Hepatic Oncology Research
- Cancer Cells and Metastasis
- Cancer Immunotherapy and Biomarkers
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
Papers in ⓘ
-
- Gene expression and cancer classification 6
- Molecular Biology Techniques and Applications 4
- TGF-β signaling in diseases 3
- Oncology 8
- Pancreatic and Hepatic Oncology Research 5
- Co-authors
- Xuning Wang (1 shared paper)Yixin Wang (1 shared paper)Wei‐Yin Loh (3 shared papers)Xu He (1 shared paper)Shawn T. Estrem (6 shared papers)Karim A. Benhadji (7 shared papers)Sandra Close (3 shared papers)Carmen M. Dumaual (1 shared paper)
- Journals
- Statistics in Medicine (3 papers)BMC Cancer (2 papers)PLoS ONE (2 papers)Pharmacogenomics (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesItalyFrance
In The Last Decade
Michael Man
23 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 125
- Oncology 343
- Statistics and Probability 102
- Pharmacology 93
- Cancer Research 117
- Internal Medicine 26
Countries citing papers authored by Michael Man
This map shows the geographic impact of Michael Man'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 Man with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Man more than expected).
Fields of papers citing papers by Michael Man
This network shows the impact of papers produced by Michael Man. 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 Man. The network helps show where Michael Man may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Man, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 170 | |
| 2 | 2021 | 149 | |
| 3 | 2000 | 128 | |
| 4 | 2015 | 111 | |
| 5 | 2019 | 77 | |
| 6 | 2020 | 46 | |
| 7 | 2007 | 46 | |
| 8 | 2004 | 43 | |
| 9 | 2002 | 41 | |
| 10 | 2023 | 36 | |
| 11 | 2007 | 30 | |
| 12 | 2019 | 26 | |
| 13 | 2017 | 25 | |
| 14 | 2015 | 22 | |
| 15 | 2006 | 20 | |
| 16 | 2016 | 16 | |
| 17 | 2004 | 12 | |
| 18 | 2013 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2018 | 4 |
About Michael Man
Michael Man is a scholar working on Molecular Biology, Oncology, Cancer Research, Statistics and Probability and Surgery, having authored 23 papers that have together received 1.0k indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Pancreatic and Hepatic Oncology Research (5 papers), Molecular Biology Techniques and Applications (4 papers), Advanced Causal Inference Techniques (4 papers), Statistical Methods in Clinical Trials (4 papers), TGF-β signaling in diseases (3 papers), Statistical Methods and Inference (3 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). The work is most often cited by research in Oncology (343 citations), Statistics and Probability (102 citations), Pharmacology (93 citations), Cancer Research (117 citations) and Internal Medicine (26 citations). Michael Man has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Xuning Wang, Yixin Wang, Wei‐Yin Loh, Xu He, Shawn T. Estrem, Karim A. Benhadji, Sandra Close, Carmen M. Dumaual, Shin Irie and Gyu Jeong Noh. Their work appears in journals such as Statistics in Medicine, BMC Cancer, PLoS ONE, Pharmacogenomics and Bioinformatics.
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.