Michael C. Gundry
- Hematology top 5%
- Acute Myeloid Leukemia Research 7
- Aging top 10%
- Molecular Biology top 10%
- CRISPR and Genetic Engineering 10
- Epigenetics and DNA Methylation 6
- Protein Degradation and Inhibitors 4
- Pluripotent Stem Cells Research 2
- Cancer Research top 10%
- Cancer Genomics and Diagnostics 3
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- CAR-T cell therapy research 5
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- Genetics and Neurodevelopmental Disorders 3
- Co-authors
- Margaret A. GoodellLorenzo BrunettiJan VijgYung‐Hsin HuangWei LiJianzhong SuXiaotian ZhangYong Lei
- Cited by
- HematologyAgingMolecular Biology
- Journals
- Nucleic Acids Research (1 paper)Nature Communications (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United StatesItalyMexico
In The Last Decade
Michael C. Gundry
23 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Hematology 318
- Aging 38
- Molecular Biology 978
- Business and International Management 22
- Cancer Research 163
Countries citing papers authored by Michael C. Gundry
This map shows the geographic impact of Michael C. Gundry'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 C. Gundry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael C. Gundry more than expected).
Fields of papers citing papers by Michael C. Gundry
This network shows the impact of papers produced by Michael C. Gundry. 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 C. Gundry. The network helps show where Michael C. Gundry may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael C. Gundry, 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 | 2024 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 1 | |
| 4 | 2021 | 6 | |
| 5 | 2021 | 14 | |
| 6 | 2019 | 29 | |
| 7 | 2018 | 10 | |
| 8 | 2018 | 46 | |
| 9 | 2018 | 195 | |
| 10 | 2018 | 21 | |
| 11 | 2017 | 157 | |
| 12 | 2017 | 0 | |
| 13 | 2017 | 11 | |
| 14 | 2017 | 168 | |
| 15 | 2017 | 16 | |
| 16 | 2016 | 189 | |
| 17 | 2016 | 132 | |
| 18 | 2016 | 6 | |
| 19 | 2012 | 56 | |
| 20 | 2011 | 67 |
About Michael C. Gundry
Michael C. Gundry is a scholar working on Hematology, Business and International Management and Molecular Biology, having authored 24 papers that have together received 1.2k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (10 papers), Acute Myeloid Leukemia Research (7 papers), Epigenetics and DNA Methylation (6 papers), CAR-T cell therapy research (5 papers), Protein Degradation and Inhibitors (4 papers), Genetics and Neurodevelopmental Disorders (3 papers), Cancer Genomics and Diagnostics (3 papers) and Pluripotent Stem Cells Research (2 papers). The work is most often cited by research in Hematology (318 citations), Aging (38 citations) and Molecular Biology (978 citations). Michael C. Gundry has collaborated with scholars based in United States, Italy and Mexico. Frequent co-authors include Margaret A. Goodell, Lorenzo Brunetti, Jan Vijg, Yung‐Hsin Huang, Wei Li, Jianzhong Su, Xiaotian Zhang, Yong Lei, Mira Jeong and Daisuke Nakada. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.
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.