Eric Wang

7.5k citations
36 papers · 3.8k indexed · 2 hit papers · h-index 22
  • Hematology top 1%
    • Acute Myeloid Leukemia Research 9
    • Protein Degradation and Inhibitors 11
    • RNA Research and Splicing 7
    • Histone Deacetylase Inhibitors Research 6
    • RNA and protein synthesis mechanisms 5
    • RNA modifications and cancer 4
    • CRISPR and Genetic Engineering 4
    • Epigenetics and DNA Methylation 3
  • Aging top 5%
  • Oncology top 10%

Eric Wang

35 papers receiving 3.7k citations

Hit Papers

Discovery of cancer drug targets by CRISPR-Cas9 screening...50020112026201620214008001.2k

Peers

Eric Wang
Comparison fields: 5 of 108
  • Hematology 1.0k
  • Molecular Biology 3.2k
  • Aging 49
  • Cancer Research 320
  • Oncology 435
Replace Yu Yao with:
Yu Yao United States
Mira Jeong United States
Ryo Kurita Japan
Michael P. Cooke United States
Lawryn H. Kasper United States
Sandra Offner Switzerland
Raúl Torres Spain
Kathrin M. Bernt United States
Jasper Mullenders Netherlands
Marianne Terndrup Pedersen Denmark
Eric Wang relative to Yu Yao United States Yu Yao's profile →
Citations per field
00.5×3.1×
Yu Yao · 1×
Citations per year

Countries citing papers authored by Eric Wang

Since Specialization
Citations

This map shows the geographic impact of Eric 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 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 Wang more than expected).

Fields of papers citing papers by Eric Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20231
2 20231
3 20231
4 20235
5 202353
6 202226
7 202221
8 202135
9 2020142
10 2019214
11 201745
12 2015109
13
Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domainsbreakdown →
2015500
14 201345
15 2013302
16 201295
17 2011207
18
RNAi screen identifies Brd4 as a therapeutic target in acute myeloid leukaemiabreakdown →
20111438
19 2009157
20 199823

About Eric Wang

Eric Wang is a scholar working on Aging, Hematology and Molecular Biology, having authored 36 papers that have together received 3.8k indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (11 papers), Acute Myeloid Leukemia Research (9 papers), RNA Research and Splicing (7 papers), Histone Deacetylase Inhibitors Research (6 papers), RNA and protein synthesis mechanisms (5 papers), RNA modifications and cancer (4 papers), CRISPR and Genetic Engineering (4 papers) and Epigenetics and DNA Methylation (3 papers). The work is most often cited by research in Hematology (1.0k citations), Molecular Biology (3.2k citations) and Aging (49 citations). Eric Wang has collaborated with scholars based in United States, Austria and Japan. Frequent co-authors include Christopher R. Vakoc, Junwei Shi, Johannes Zuber, Amy Rappaport, Iannis Aifantis, Meredith J. Taylor, Joseph P. Milazzo, Justin B. Kinney, Scott C. Kogan and Scott W. Lowe. Their work appears in journals such as Blood, Molecular Cell, Nature, Nature Biotechnology and Trends in cancer.

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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