Ting Yan
Impact in
- Analytical Chemistry top 10%
- Spectroscopy and Chemometric Analyses
Papers in
-
- Gut microbiota and health 2
- Glycosylation and Glycoproteins Research 1
-
- AI in cancer detection 2
- Co-authors
- Xiaohui Lu (3 shared papers)Cheng Zhang (3 shared papers)Guodong Lu (3 shared papers)Xiaolin Tang (2 shared papers)Jingru Yang (2 shared papers)Jin Wang (1 shared paper)Wen‐Cui Li (1 shared paper)Bincheng Huang (2 shared papers)
- Journals
- Complex & Intelligent Systems (2 papers)Applied Microbiology and Biotechnology (1 paper)Kidney & Blood Pressure Research (1 paper)Vascular (1 paper)Computers and Electronics in Agriculture (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Ting Yan
15 papers receiving 226 citations
Peers
Comparison fields: 5 of 74
- Analytical Chemistry 70
- Internal Medicine 13
- Biophysics 15
- Computational Mathematics 1
- Pathology and Forensic Medicine 26
Countries citing papers authored by Ting Yan
This map shows the geographic impact of Ting 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 Ting Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting Yan more than expected).
Fields of papers citing papers by Ting Yan
This network shows the impact of papers produced by Ting 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 Ting Yan. The network helps show where Ting Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ting 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 | 2021 | 67 | |
| 2 | 2016 | 30 | |
| 3 | 2019 | 23 | |
| 4 | 2023 | 20 | |
| 5 | 2021 | 18 | |
| 6 | 2020 | 16 | |
| 7 | 2024 | 11 | |
| 8 | 2022 | 10 | |
| 9 | 2024 | 9 | |
| 10 | 2020 | 7 | |
| 11 | 2024 | 6 | |
| 12 | 2018 | 5 | |
| 13 | [Analysis of body composition in patients with Crohn's disease]. | 2014 | 3 |
| 14 | 2021 | 3 | |
| 15 | 2021 | 2 | |
| 16 | 2023 | 0 |
About Ting Yan
Ting Yan is a scholar working on Molecular Biology, Artificial Intelligence, Genetics, Computer Vision and Pattern Recognition and Oncology, having authored 16 papers that have together received 230 indexed citations. Recurring topics across this work include Inflammatory Bowel Disease (3 papers), Gut microbiota and health (2 papers), Spectroscopy and Chemometric Analyses (2 papers), AI in cancer detection (2 papers), Venous Thromboembolism Diagnosis and Management (1 paper), Glycosylation and Glycoproteins Research (1 paper), Advanced Technology in Applications (1 paper) and Maternal Mental Health During Pregnancy and Postpartum (1 paper). The work is most often cited by research in Analytical Chemistry (70 citations), Internal Medicine (13 citations), Biophysics (15 citations), Computational Mathematics (1 citation) and Pathology and Forensic Medicine (26 citations). Ting Yan has collaborated with scholars based in China and United States. Frequent co-authors include Xiaohui Lu, Cheng Zhang, Guodong Lu, Xiaolin Tang, Jingru Yang, Jin Wang, Wen‐Cui Li, Bincheng Huang, Jin Wang and Zhongkui Xia. Their work appears in journals such as Complex & Intelligent Systems, Applied Microbiology and Biotechnology, Kidney & Blood Pressure Research, Vascular and Computers and Electronics in Agriculture.
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.