Hang Shi
- Physiology top 0.5%
- Adipose Tissue and Metabolism 41
- Epidemiology top 0.5%
- Adipokines, Inflammation, and Metabolic Diseases 30
- Liver Disease Diagnosis and Treatment 8
- Biochemistry top 0.5%
- Lipid metabolism and biosynthesis 14
- Immunology top 1%
- Immune cells in cancer 10
- Immune Cell Function and Interaction 8
-
- Epigenetics and DNA Methylation 13
-
- Endoplasmic Reticulum Stress and Disease 8
- Co-authors
- Jeffrey S. FlierIphigenia TzameliKaren InouyeMaia V. KokoevaHuali YinBingzhong XueMichael B. ZemelDouglas B. DiRienzo
- Cited by
- PhysiologyEpidemiologyBiochemistry
- Partner nations
- United StatesChinaGeorgia
In The Last Decade
Hang Shi
101 papers receiving 9.2k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Physiology 3.6k
- Epidemiology 3.1k
- Biochemistry 611
- Endocrine and Autonomic Systems 528
- Immunology 1.6k
Countries citing papers authored by Hang Shi
This map shows the geographic impact of Hang Shi'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 Hang Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Shi more than expected).
Fields of papers citing papers by Hang Shi
This network shows the impact of papers produced by Hang Shi. 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 Hang Shi. The network helps show where Hang Shi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hang Shi, 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 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 4 | |
| 7 | 2023 | 3 | |
| 8 | 2021 | 38 | |
| 9 | 2020 | 15 | |
| 10 | 2018 | 19 | |
| 11 | 2017 | 198 | |
| 12 | 2016 | 22 | |
| 13 | 2015 | 37 | |
| 14 | 2015 | 32 | |
| 15 | 2012 | 52 | |
| 16 | 2010 | 125 | |
| 17 | 2009 | 226 | |
| 18 | 2008 | 134 | |
| 19 | TLR4 links innate immunity and fatty acid–induced insulin resistancebreakdown → | 2006 | 2863 |
| 20 | 2004 | 187 |
About Hang Shi
Hang Shi is a scholar working on Biochemistry, Physiology, Geriatrics and Gerontology, Epidemiology and Endocrine and Autonomic Systems, having authored 103 papers that have together received 9.4k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (41 papers), Adipokines, Inflammation, and Metabolic Diseases (30 papers), Lipid metabolism and biosynthesis (14 papers), Epigenetics and DNA Methylation (13 papers), Immune cells in cancer (10 papers), Liver Disease Diagnosis and Treatment (8 papers), Endoplasmic Reticulum Stress and Disease (8 papers) and Immune Cell Function and Interaction (8 papers). The work is most often cited by research in Physiology (3.6k citations), Epidemiology (3.1k citations), Biochemistry (611 citations), Endocrine and Autonomic Systems (528 citations) and Immunology (1.6k citations). Hang Shi has collaborated with scholars based in United States, China and Georgia. Frequent co-authors include Jeffrey S. Flier, Iphigenia Tzameli, Karen Inouye, Maia V. Kokoeva, Huali Yin, Bingzhong Xue, Michael B. Zemel, Douglas B. DiRienzo, Liqing Yu and Zhenggang Yang. Their work appears in journals such as Journal of Biological Chemistry, The FASEB Journal, PLoS ONE, Nature Communications and Endocrinology.
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.