Matthew MacKay
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- Aging top 5%
Papers in
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- Single-cell and spatial transcriptomics 4
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- Spaceflight effects on biology 7
- Co-authors
- Christopher E. Mason (16 shared papers)Ari Melnick (7 shared papers)Francine E. Garrett-Bakelman (5 shared papers)Christopher Famulare (2 shared papers)Ly Vu (2 shared papers)Jessica Schulman (1 shared paper)Virginia M. Klimek (1 shared paper)Samie R. Jaffrey (2 shared papers)
- Journals
- Cell Reports (5 papers)Blood (2 papers)Nature Communications (2 papers)Patterns (1 paper)JAMA Network Open (1 paper)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Matthew MacKay
20 papers receiving 1.7k citations
Matthew MacKay's Hit Papers
Peers
Comparison fields: 5 of 91
- Cancer Research 582
- Aging 55
- Molecular Biology 1.2k
- Oncology 378
- Physiology 203
Countries citing papers authored by Matthew MacKay
This map shows the geographic impact of Matthew MacKay'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 Matthew MacKay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew MacKay more than expected).
Fields of papers citing papers by Matthew MacKay
This network shows the impact of papers produced by Matthew MacKay. 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 Matthew MacKay. The network helps show where Matthew MacKay may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew MacKay, 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 | The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells Hit paper breakdown → | 2017 | 932 |
| 2 | 2020 | 165 | |
| 3 | 2021 | 142 | |
| 4 | 2019 | 86 | |
| 5 | 2020 | 59 | |
| 6 | 2020 | 57 | |
| 7 | 2019 | 49 | |
| 8 | 2020 | 41 | |
| 9 | 2020 | 36 | |
| 10 | 2024 | 31 | |
| 11 | 2019 | 24 | |
| 12 | 2022 | 16 | |
| 13 | 2013 | 11 | |
| 14 | 2020 | 11 | |
| 15 | 2024 | 9 | |
| 16 | 2022 | 9 | |
| 17 | 2021 | 7 | |
| 18 | 2024 | 6 | |
| 19 | 2017 | 2 | |
| 20 | 2023 | 1 |
About Matthew MacKay
Matthew MacKay is a scholar working on Molecular Biology, Physiology, Cancer Research, Pathology and Forensic Medicine and Genetics, having authored 20 papers that have together received 1.7k indexed citations. Recurring topics across this work include Spaceflight effects on biology (7 papers), Cancer Genomics and Diagnostics (7 papers), Single-cell and spatial transcriptomics (4 papers), Genetic factors in colorectal cancer (3 papers), Acute Myeloid Leukemia Research (3 papers), High Altitude and Hypoxia (3 papers), CAR-T cell therapy research (2 papers) and Genetics, Aging, and Longevity in Model Organisms (2 papers). The work is most often cited by research in Cancer Research (582 citations), Aging (55 citations), Molecular Biology (1.2k citations), Oncology (378 citations) and Physiology (203 citations). Matthew MacKay has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Christopher E. Mason, Ari Melnick, Francine E. Garrett-Bakelman, Christopher Famulare, Ly Vu, Jessica Schulman, Virginia M. Klimek, Samie R. Jaffrey, Brian F. Pickering and Yuanming Cheng. Their work appears in journals such as Cell Reports, Blood, Nature Communications, Patterns and JAMA Network Open.
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.