Eric S. Wang

2.8k citations
18 papers · 851 · h-index 10

Impact in

  • Hematology top 5%
    • Multiple Myeloma Research and Treatments
  • Oncology top 10%
    • Peptidase Inhibition and Analysis
    • Cancer-related Molecular Pathways

Papers in

    • Protein Degradation and Inhibitors 14
    • Ubiquitin and proteasome pathways 8
    • Glycosylation and Glycoproteins Research 1

Eric S. Wang

16 papers receiving 829 citations

Peers

Eric S. Wang
Comparison fields: 5 of 49
  • Hematology 197
  • Oncology 357
  • Molecular Biology 728
  • Genetics 68
  • Pulmonary and Respiratory Medicine 100
Replace Alexandru D. Buhimschi with:
Alexandru D. Buhimschi United States
Matthias Brand Germany
Dhanusha A. Nalawansha United States
Chu Myong Seong South Korea
Elisabeth Walsby United Kingdom
Marja Dubay United States
Heather Kostner United States
Ann Katrin Greifenberg Germany
Yung Kiang Loh Singapore
Eric S. Wang relative to Alexandru D. Buhimschi United States Alexandru D. Buhimschi's profile →
Citations per field
00.5×3.7×
Alexandru D. Buhimschi · 1×
Citations per year

Countries citing papers authored by Eric S. Wang

Since Specialization
Citations

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

Fields of papers citing papers by Eric S. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Eric S. Wang, 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 Eric S. Wang Line = papers co-authored together Eric S. Wang links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2019219
2 2018211
3 2018138
4 202182
5 202070
6 201868
7 201911
8 202211
9 202210
10 20229
11 20066
12 20115
13 20165
14 20234
15 20241
16 20251
17 20250
18 20230

About Eric S. Wang

Eric S. Wang is a scholar working on Molecular Biology, Oncology, Cell Biology, Epidemiology and Hematology, having authored 18 papers that have together received 851 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (14 papers), Ubiquitin and proteasome pathways (8 papers), Multiple Myeloma Research and Treatments (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Autophagy in Disease and Therapy (2 papers), Glycosylation and Glycoproteins Research (1 paper), Cellular transport and secretion (1 paper) and melanin and skin pigmentation (1 paper). The work is most often cited by research in Hematology (197 citations), Oncology (357 citations), Molecular Biology (728 citations), Genetics (68 citations) and Pulmonary and Respiratory Medicine (100 citations). Eric S. Wang has collaborated with scholars based in United States, Hong Kong and Austria. Frequent co-authors include Nathanael S. Gray, Eric S. Fischer, Katherine A. Donovan, Tinghu Zhang, Baishan Jiang, Yanke Liang, Radosław P. Nowak, Nicholas Kwiatkowski, Matthias Brand and Georg E. Winter. Their work appears in journals such as Nature Chemical Biology, ACS Chemical Biology, Cell chemical biology, Angewandte Chemie International Edition and Behavioral Sciences & the Law.

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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