Eric Wen Su
- Molecular Biology top 10%
- Gene expression and cancer classification 7
- Bioinformatics and Genomic Networks 5
- Biomedical Text Mining and Ontologies 3
- Molecular Biology Techniques and Applications 3
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- Chemokine receptors and signaling 2
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- Cancer Genomics and Diagnostics 3
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- Computational Drug Discovery Methods 3
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- Pharmacogenetics and Drug Metabolism 2
- Co-authors
- Vladimir N. UverskyJiangang LiuChristopher J. OldfieldA. Keith DunkerNarayanan B. PerumalJian WangSheng-Bin PengDonald C. Paul
- Cited by
- Molecular BiologyOncologyImmunology
- Journals
- Journal of Clinical Oncology (2 papers)Gene (1 paper)Molecular Diagnosis & Therapy (1 paper)
- Partner nations
- United StatesIsraelSpain
In The Last Decade
Eric Wen Su
19 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Molecular Biology 779
- Oncology 230
- Immunology 151
- Cancer Research 106
- Endocrinology, Diabetes and Metabolism 99
Countries citing papers authored by Eric Wen Su
This map shows the geographic impact of Eric Wen Su'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 Eric Wen Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Wen Su more than expected).
Fields of papers citing papers by Eric Wen Su
This network shows the impact of papers produced by Eric Wen Su. 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 Eric Wen Su. The network helps show where Eric Wen Su may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eric Wen Su, 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 | 2022 | 44 | |
| 2 | 2021 | 1 | |
| 3 | 2021 | 34 | |
| 4 | 2018 | 1 | |
| 5 | 2017 | 20 | |
| 6 | 2011 | 58 | |
| 7 | 2008 | 0 | |
| 8 | 2007 | 16 | |
| 9 | 2007 | 7 | |
| 10 | 2007 | 11 | |
| 11 | 2006 | 170 | |
| 12 | 2006 | 7 | |
| 13 | 2006 | 48 | |
| 14 | Intrinsic Disorder in Transcription Factorsbreakdown → | 2006 | 592 |
| 15 | 2006 | 2 | |
| 16 | 2005 | 65 | |
| 17 | 2005 | 34 | |
| 18 | 2005 | 8 | |
| 19 | 2004 | 34 | |
| 20 | 2003 | 45 |
About Eric Wen Su
Eric Wen Su is a scholar working on Cancer Research, Pharmacology, Computational Theory and Mathematics, Molecular Biology and Oncology, having authored 20 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (7 papers), Bioinformatics and Genomic Networks (5 papers), Biomedical Text Mining and Ontologies (3 papers), Computational Drug Discovery Methods (3 papers), Molecular Biology Techniques and Applications (3 papers), Cancer Genomics and Diagnostics (3 papers), Pharmacogenetics and Drug Metabolism (2 papers) and Chemokine receptors and signaling (2 papers). The work is most often cited by research in Molecular Biology (779 citations), Oncology (230 citations), Immunology (151 citations), Cancer Research (106 citations) and Endocrinology, Diabetes and Metabolism (99 citations). Eric Wen Su has collaborated with scholars based in United States, Israel and Spain. Frequent co-authors include Vladimir N. Uversky, Jiangang Liu, Christopher J. Oldfield, A. Keith Dunker, Narayanan B. Perumal, Jian Wang, Sheng-Bin Peng, Donald C. Paul, S Kovacevic and James Schrementi. Their work appears in journals such as Journal of Clinical Oncology, Gene, Molecular Diagnosis & Therapy, Molecular Genetics and Metabolism and JCO Precision Oncology.
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.