Michael Q. Ding
Impact in
- Hepatology top 10%
- Liver physiology and pathology
Papers in
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- Gene expression and cancer classification 1
- Bioinformatics and Genomic Networks 1
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- Liver Disease Diagnosis and Treatment 2
- Co-authors
- Xinghua Lu (3 shared papers)Gregory F. Cooper (1 shared paper)Lujia Chen (1 shared paper)Anne Orr (2 shared papers)Donna B. Stolz (2 shared papers)George K. Michalopoulos (2 shared papers)William C. Bowen (2 shared papers)Josiah E. Radder (1 shared paper)
- Journals
- PLoS ONE (2 papers)npj Systems Biology and Applications (1 paper)BMC Health Services Research (1 paper)Molecular Cancer Research (1 paper)Aging Cell (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Michael Q. Ding
8 papers receiving 295 citations
Peers
Comparison fields: 5 of 77
- Hepatology 48
- Health Informatics 5
- Computational Theory and Mathematics 46
- Cancer Research 37
- Endocrine and Autonomic Systems 16
Countries citing papers authored by Michael Q. Ding
This map shows the geographic impact of Michael Q. Ding'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 Q. Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Q. Ding more than expected).
Fields of papers citing papers by Michael Q. Ding
This network shows the impact of papers produced by Michael Q. Ding. 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 Q. Ding. The network helps show where Michael Q. Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Q. Ding, 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 | 2017 | 115 | |
| 2 | 2014 | 104 | |
| 3 | 2017 | 29 | |
| 4 | 2014 | 21 | |
| 5 | 2016 | 16 | |
| 6 | 2020 | 10 | |
| 7 | 2021 | 1 | |
| 8 | Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual Attention | 2020 | 1 |
| 9 | 2023 | 0 |
About Michael Q. Ding
Michael Q. Ding is a scholar working on Molecular Biology, Epidemiology, Computational Theory and Mathematics, Hepatology and Infectious Diseases, having authored 9 papers that have together received 297 indexed citations. Recurring topics across this work include Liver physiology and pathology (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Computational Drug Discovery Methods (2 papers), HER2/EGFR in Cancer Research (1 paper), Cancer Genomics and Diagnostics (1 paper), Gene expression and cancer classification (1 paper), Drug-Induced Hepatotoxicity and Protection (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Hepatology (48 citations), Health Informatics (5 citations), Computational Theory and Mathematics (46 citations), Cancer Research (37 citations) and Endocrine and Autonomic Systems (16 citations). Michael Q. Ding has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xinghua Lu, Gregory F. Cooper, Lujia Chen, Anne Orr, Donna B. Stolz, George K. Michalopoulos, William C. Bowen, Josiah E. Radder, Liang‐I Kang and Yu Hsuan Carol Yang. Their work appears in journals such as PLoS ONE, npj Systems Biology and Applications, BMC Health Services Research, Molecular Cancer Research and Aging Cell.
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.