Matthew Ung
Impact in
- Cancer Research top 10%
- Cancer, Lipids, and Metabolism
- Cancer, Hypoxia, and Metabolism
- Cancer-related molecular mechanisms research
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- RNA modifications and cancer
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
Papers in
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- Gene expression and cancer classification 6
- Bioinformatics and Genomic Networks 5
- Genomics and Chromatin Dynamics 5
- CRISPR and Genetic Engineering 4
- RNA modifications and cancer 3
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- Cancer-related molecular mechanisms research 3
- Cancer, Hypoxia, and Metabolism 3
- Cancer, Lipids, and Metabolism 2
- Co-authors
- Chao Cheng (26 shared papers)Jie Tan (2 shared papers)Casey S. Greene (2 shared papers)Jason H. Moore (1 shared paper)James DiRenzo (3 shared papers)Nicholas R. De Lay (1 shared paper)Erik Andrews (3 shared papers)Yongqiang Fan (1 shared paper)
- Journals
- Molecular Cancer Research (3 papers)Nucleic Acids Research (2 papers)Blood (2 papers)Cancer Research (2 papers)PLoS Computational Biology (2 papers)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Matthew Ung
33 papers receiving 792 citations
Peers
Comparison fields: 5 of 108
- Cancer Research 223
- Molecular Biology 474
- Oncology 131
- Health Informatics 5
- Biophysics 22
Countries citing papers authored by Matthew Ung
This map shows the geographic impact of Matthew Ung'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 Ung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Ung more than expected).
Fields of papers citing papers by Matthew Ung
This network shows the impact of papers produced by Matthew Ung. 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 Ung. The network helps show where Matthew Ung may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Ung, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 158 | |
| 2 | 2014 | 122 | |
| 3 | 2014 | 97 | |
| 4 | 2015 | 75 | |
| 5 | 2015 | 62 | |
| 6 | 2014 | 43 | |
| 7 | 2016 | 29 | |
| 8 | 2018 | 27 | |
| 9 | 2014 | 25 | |
| 10 | 2015 | 21 | |
| 11 | 2017 | 19 | |
| 12 | 2015 | 18 | |
| 13 | 2015 | 16 | |
| 14 | 2017 | 12 | |
| 15 | 2017 | 10 | |
| 16 | 2016 | 9 | |
| 17 | 2015 | 8 | |
| 18 | 2017 | 8 | |
| 19 | 2016 | 6 | |
| 20 | 2016 | 5 |
About Matthew Ung
Matthew Ung is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Oncology and Genetics, having authored 33 papers that have together received 801 indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Bioinformatics and Genomic Networks (5 papers), Genomics and Chromatin Dynamics (5 papers), CRISPR and Genetic Engineering (4 papers), RNA modifications and cancer (3 papers), Cancer-related molecular mechanisms research (3 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer, Lipids, and Metabolism (2 papers). The work is most often cited by research in Cancer Research (223 citations), Molecular Biology (474 citations), Oncology (131 citations), Health Informatics (5 citations) and Biophysics (22 citations). Matthew Ung has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Chao Cheng, Jie Tan, Casey S. Greene, Jason H. Moore, James DiRenzo, Nicholas R. De Lay, Erik Andrews, Yongqiang Fan, Jiqiang Ling and Jiang Wu. Their work appears in journals such as Molecular Cancer Research, Nucleic Acids Research, Blood, Cancer Research and PLoS Computational Biology.
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.