Ying E. Zhang
- Molecular Biology top 0.2%
- TGF-β signaling in diseases 48
- Cancer-related gene regulation 14
- ATP Synthase and ATPases Research 13
- Kruppel-like factors research 11
- RNA modifications and cancer 8
- Hedgehog Signaling Pathway Studies 7
- Cancer Research top 0.5%
- NF-κB Signaling Pathways 7
- Oncology top 0.5%
- Immunology and Allergy top 0.5%
- Hepatology top 1%
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- Genetic factors in colorectal cancer 10
- Co-authors
- Rik DerynckXin‐Hua FengRui-Yun WuMotozo YamashitaRobert FillingameXiangchun WangThomas J. MusciAli Hemmati‐Brivanlou
- Partner nations
- United StatesChinaGermany
In The Last Decade
Ying E. Zhang
100 papers receiving 16.2k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Molecular Biology 12.5k
- Cancer Research 2.4k
- Oncology 3.5k
- Immunology and Allergy 665
- Hepatology 642
Countries citing papers authored by Ying E. Zhang
This map shows the geographic impact of Ying E. Zhang'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 Ying E. Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying E. Zhang more than expected).
Fields of papers citing papers by Ying E. Zhang
This network shows the impact of papers produced by Ying E. Zhang. 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 Ying E. Zhang. The network helps show where Ying E. Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying E. Zhang, 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 | 14 | |
| 2 | 2022 | 5 | |
| 3 | 2020 | 4 | |
| 4 | 2018 | 22 | |
| 5 | 2018 | 58 | |
| 6 | 2018 | 63 | |
| 7 | 2015 | 40 | |
| 8 | 2015 | 16 | |
| 9 | 2014 | 11 | |
| 10 | Image-based genome-wide siRNA screen identifies selective autophagy factorsbreakdown → | 2011 | 385 |
| 11 | 2010 | 81 | |
| 12 | 2009 | 64 | |
| 13 | 2008 | 476 | |
| 14 | 2007 | 83 | |
| 15 | 2006 | 54 | |
| 16 | 2003 | 52 | |
| 17 | Smad-dependent and Smad-independent pathways in TGF-β family signallingbreakdown → | 2003 | 4493 |
| 18 | 2000 | 109 | |
| 19 | Receptor-associated Mad homologues synergize as effectors of the TGF-β responsebreakdown → | 1996 | 760 |
| 20 | 1996 | 142 |
About Ying E. Zhang
Ying E. Zhang is a scholar working on Molecular Biology, Cancer Research, Pathology and Forensic Medicine, Oncology and Immunology and Allergy, having authored 102 papers that have together received 16.4k indexed citations. Recurring topics across this work include TGF-β signaling in diseases (48 papers), Cancer-related gene regulation (14 papers), ATP Synthase and ATPases Research (13 papers), Kruppel-like factors research (11 papers), Genetic factors in colorectal cancer (10 papers), RNA modifications and cancer (8 papers), Hedgehog Signaling Pathway Studies (7 papers) and NF-κB Signaling Pathways (7 papers). The work is most often cited by research in Molecular Biology (12.5k citations), Cancer Research (2.4k citations), Oncology (3.5k citations), Immunology and Allergy (665 citations) and Hepatology (642 citations). Ying E. Zhang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Rik Derynck, Xin‐Hua Feng, Rui-Yun Wu, Motozo Yamashita, Robert Fillingame, Xiangchun Wang, Thomas J. Musci, Ali Hemmati‐Brivanlou, Daniel J. Gehling and Chenbei Chang. Their work appears in journals such as Journal of Biological Chemistry, Nature, Cancer Research, International Journal of Molecular Sciences and Oncogene.
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.