Y. Eric Shi

21 papers receiving 885 citations

Peers

Y. Eric Shi
Comparison fields: 5 of 85
  • Cancer Research 413
  • Hematology 157
  • Oncology 330
  • Immunology and Allergy 60
  • Neurology 107
Replace Antonella Tacconelli with:
Antonella Tacconelli Italy
F. van Valen Germany
Lucia Cappabianca Italy
Shou‐Ih Hu United States
Kay M. Southgate United Kingdom
Omar Benzakour United Kingdom
Olivier Robledo Canada
Sean Garrison United States
Masahiro Sato Japan
Jan‐Marcus Daniel Germany
Y. Eric Shi relative to Antonella Tacconelli Italy Antonella Tacconelli's profile →
Citations per field
00.5×2.7×
Antonella Tacconelli · 1×
Citations per year

Countries citing papers authored by Y. Eric Shi

Since Specialization
Citations

This map shows the geographic impact of Y. Eric 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 Y. Eric Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y. Eric Shi more than expected).

Fields of papers citing papers by Y. Eric Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Y. Eric 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 Y. Eric Shi. The network helps show where Y. Eric Shi may publish in the future.

Co-authors

The 25 scholars most cited alongside Y. Eric Shi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Y. Eric Shi Line = papers co-authored together Y. Eric Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997135
2 1997127
3 1997110
4 200482
5 199966
6
Stimulation of estrogen receptor signaling by gamma synuclein.
200356
7 199954
8 200651
9 200039
10 200230
11 201030
12 200624
13 201422
14 200720
15 201314
16 200311
17 19999
18 20147
19 20244
20 19953

About Y. Eric Shi

Y. Eric Shi is a scholar working on Molecular Biology, Cancer Research, Oncology, Hematology and Cellular and Molecular Neuroscience, having authored 22 papers that have together received 897 indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (8 papers), Blood Coagulation and Thrombosis Mechanisms (5 papers), Nuclear Receptors and Signaling (4 papers), Peptidase Inhibition and Analysis (4 papers), Heat shock proteins research (3 papers), Parkinson's Disease Mechanisms and Treatments (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Cell Adhesion Molecules Research (2 papers). The work is most often cited by research in Cancer Research (413 citations), Hematology (157 citations), Oncology (330 citations), Immunology and Allergy (60 citations) and Neurology (107 citations). Y. Eric Shi has collaborated with scholars based in United States, China and India. Frequent co-authors include Yiliang E. Liu, Ming‐Sheng Wang, Itzhak D. Goldberg, Yangfu Jiang, Qing‐Xiang Amy Sang, J. M. Greene, Shijie Sheng, Christopher M. Overall, Heather F. Bigg and Bjorn Steffensen. Their work appears in journals such as Journal of Biological Chemistry, Oncogene, Breast Cancer Research and Treatment, Molecular Oncology and FEBS Journal.

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.

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