Jim Yan
Impact in
- Epidemiology top 10%
- Liver Disease Diagnosis and Treatment
-
- Diet, Metabolism, and Disease
Papers in
- Oncology 3
- Co-authors
- Jacquelyn J. Maher (5 shared papers)Scott Turner (2 shared papers)Lorenzo Arnaboldi (1 shared paper)Robert E. Pitas (1 shared paper)Thomas M. Badger (1 shared paper)Ray Kit Ng (1 shared paper)James P. Grenert (2 shared papers)Raymond Ng (2 shared papers)
- Journals
- Journal of Lipid Research (3 papers)Journal of Hepatology (1 paper)Gastroenterology (1 paper)Journal of Clinical Pathology (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jim Yan
15 papers receiving 583 citations
Peers
Comparison fields: 5 of 80
- Epidemiology 282
- Endocrinology, Diabetes and Metabolism 118
- Hepatology 51
- Cell Biology 79
- Physiology 115
Countries citing papers authored by Jim Yan
This map shows the geographic impact of Jim Yan'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 Jim Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jim Yan more than expected).
Fields of papers citing papers by Jim Yan
This network shows the impact of papers produced by Jim Yan. 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 Jim Yan. The network helps show where Jim Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jim Yan, 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 | 2006 | 222 | |
| 2 | 1999 | 84 | |
| 3 | 2009 | 77 | |
| 4 | 2007 | 54 | |
| 5 | 2010 | 46 | |
| 6 | 2012 | 35 | |
| 7 | 2015 | 17 | |
| 8 | 2005 | 15 | |
| 9 | 2013 | 11 | |
| 10 | 2013 | 10 | |
| 11 | 2022 | 8 | |
| 12 | 2024 | 4 | |
| 13 | 2020 | 4 | |
| 14 | Multi-ethnic comparisons of genome-wide alterations in breast cancer using paraffin embedded samples. | 2007 | 2 |
| 15 | 2021 | 2 |
About Jim Yan
Jim Yan is a scholar working on Molecular Biology, Oncology, Epidemiology, Infectious Diseases and Pediatrics, Perinatology and Child Health, having authored 15 papers that have together received 591 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Traffic control and management (2 papers), Prenatal Screening and Diagnostics (2 papers), Sarcoma Diagnosis and Treatment (1 paper), Alzheimer's disease research and treatments (1 paper), Folate and B Vitamins Research (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Epidemiology (282 citations), Endocrinology, Diabetes and Metabolism (118 citations), Hepatology (51 citations), Cell Biology (79 citations) and Physiology (115 citations). Jim Yan has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Jacquelyn J. Maher, Scott Turner, Lorenzo Arnaboldi, Robert E. Pitas, Thomas M. Badger, Ray Kit Ng, James P. Grenert, Raymond Ng, Li Gan and Daseng Yang. Their work appears in journals such as Journal of Lipid Research, Journal of Hepatology, Gastroenterology, Journal of Clinical Pathology and Proceedings of the National Academy of Sciences.
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.