Sujun Hua
Impact in
- Cancer Research top 1%
- Cancer, Hypoxia, and Metabolism
- Molecular Biology top 2%
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Epigenetics and DNA Methylation
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- RNA modifications and cancer
Papers in
-
- Genomics and Chromatin Dynamics 5
- RNA Research and Splicing 3
- RNA and protein synthesis mechanisms 3
- Epigenetics and DNA Methylation 2
- Bioinformatics and Genomic Networks 2
- Retinoids in leukemia and cellular processes 2
- Protein Structure and Dynamics 2
- Machine Learning in Bioinformatics 2
- Co-authors
- Zhirong Sun (3 shared papers)Ronald A. DePinho (3 shared papers)Ralf Kittler (2 shared papers)K White (2 shared papers)Ng Shyh‐Chang (1 shared paper)Rushika M. Perera (1 shared paper)Haoqiang Ying (1 shared paper)Matteo Ligorio (1 shared paper)
- Journals
- Journal of Molecular Biology (2 papers)Science (2 papers)Molecular Systems Biology (1 paper)Bioinformatics (1 paper)Cell Reports (1 paper)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Sujun Hua
14 papers receiving 3.8k citations
Sujun Hua's Hit Papers
Peers
Comparison fields: 5 of 135
- Cancer Research 1.2k
- Molecular Biology 2.8k
- Biochemistry 166
- Oncology 519
- Aging 28
Countries citing papers authored by Sujun Hua
This map shows the geographic impact of Sujun Hua'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 Sujun Hua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujun Hua more than expected).
Fields of papers citing papers by Sujun Hua
This network shows the impact of papers produced by Sujun Hua. 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 Sujun Hua. The network helps show where Sujun Hua may publish in the future.
Co-authors
The 25 scholars most cited alongside Sujun Hua, 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 | Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway Hit paper breakdown → | 2013 | 1564 |
| 2 | Support vector machine approach for protein subcellular localization prediction Hit paper breakdown → | 2001 | 728 |
| 3 | 2001 | 435 | |
| 4 | 2009 | 256 | |
| 5 | 2004 | 250 | |
| 6 | 2008 | 157 | |
| 7 | 2010 | 119 | |
| 8 | 2009 | 104 | |
| 9 | 2009 | 84 | |
| 10 | 2013 | 61 | |
| 11 | 2013 | 61 | |
| 12 | 2004 | 31 | |
| 13 | 2006 | 19 | |
| 14 | 2002 | 8 |
About Sujun Hua
Sujun Hua is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Plant Science, Cellular and Molecular Neuroscience and Ecology, Evolution, Behavior and Systematics, having authored 14 papers that have together received 3.9k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (5 papers), RNA Research and Splicing (3 papers), RNA and protein synthesis mechanisms (3 papers), Epigenetics and DNA Methylation (2 papers), Bioinformatics and Genomic Networks (2 papers), Retinoids in leukemia and cellular processes (2 papers), Protein Structure and Dynamics (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Cancer Research (1.2k citations), Molecular Biology (2.8k citations), Biochemistry (166 citations), Oncology (519 citations) and Aging (28 citations). Sujun Hua has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Zhirong Sun, Ronald A. DePinho, Ralf Kittler, K White, Ng Shyh‐Chang, Rushika M. Perera, Haoqiang Ying, Matteo Ligorio, Marcia C. Haigis and John M. Asara. Their work appears in journals such as Journal of Molecular Biology, Science, Molecular Systems Biology, Bioinformatics and Cell Reports.
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.