Eric Wang

7.5k total citations · 2 hit papers
36 papers, 3.8k citations indexed

About

Eric Wang is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Eric Wang has authored 36 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 12 papers in Hematology and 3 papers in Oncology. Recurrent topics in Eric Wang's work include Protein Degradation and Inhibitors (11 papers), Acute Myeloid Leukemia Research (9 papers) and RNA Research and Splicing (7 papers). Eric Wang is often cited by papers focused on Protein Degradation and Inhibitors (11 papers), Acute Myeloid Leukemia Research (9 papers) and RNA Research and Splicing (7 papers). Eric Wang collaborates with scholars based in United States, Austria and Japan. Eric Wang's co-authors include Christopher R. Vakoc, Junwei Shi, Johannes Zuber, Meredith J. Taylor, Amy Rappaport, Iannis Aifantis, Joseph P. Milazzo, Justin B. Kinney, Scott W. Lowe and Scott C. Kogan and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Eric Wang

35 papers receiving 3.7k citations

Hit Papers

RNAi screen identifies Brd4 as a therapeutic target in ac... 2011 2026 2016 2021 2011 2015 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eric Wang United States 22 3.2k 1.0k 435 320 300 36 3.8k
Kathrin M. Bernt United States 23 1.8k 0.6× 683 0.7× 453 1.0× 147 0.5× 80 0.3× 58 2.4k
Lawryn H. Kasper United States 22 2.7k 0.9× 458 0.4× 501 1.2× 387 1.2× 131 0.4× 26 3.6k
Sandra Offner Switzerland 25 2.7k 0.8× 1.4k 1.3× 600 1.4× 324 1.0× 236 0.8× 37 4.5k
Valeria Tosello Italy 26 1.5k 0.5× 555 0.5× 782 1.8× 328 1.0× 179 0.6× 59 3.1k
Marianne Terndrup Pedersen Denmark 17 1.9k 0.6× 246 0.2× 441 1.0× 188 0.6× 83 0.3× 26 2.6k
Mira Jeong United States 28 2.8k 0.9× 1.7k 1.6× 264 0.6× 593 1.9× 83 0.3× 47 4.1k
Ryo Kurita Japan 25 2.5k 0.8× 707 0.7× 182 0.4× 219 0.7× 478 1.6× 83 3.6k
Yu Yao United States 25 1.8k 0.6× 335 0.3× 187 0.4× 659 2.1× 124 0.4× 71 2.4k
César Cobaleda Spain 21 1.3k 0.4× 483 0.5× 695 1.6× 294 0.9× 84 0.3× 60 2.7k
Salvatore Spicuglia France 30 2.1k 0.7× 217 0.2× 272 0.6× 505 1.6× 118 0.4× 83 2.9k

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 of co-authors of Eric Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Wang. A scholar is included among the top collaborators of Eric Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eric Wang. Eric Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Benbarche, Salima, Bo Liu, Jeetayu Biswas, et al.. (2023). Synthetic Introns Identify the Novel RNA Splicing Factor GPATCH8 As Required for Mis-Splicing Induced By SF3B1 Mutations. Blood. 142(Supplement 1). 3–3. 1 indexed citations
3.
Wang, Eric, et al.. (2023). Abstract A04: Modulation of RNA splicing enhances response to BCL2 inhibition in leukemia. Blood Cancer Discovery. 4(3_Supplement). A04–A04. 1 indexed citations
4.
Beckedorff, Felipe, Tulasigeri M. Totiger, Maurizio Affer, et al.. (2023). Altered RNA Export in SF3B1 Mutants Increases Sensitivity to Nuclear Export Inhibition. Blood. 142(Supplement 1). 44–44. 1 indexed citations
5.
Tan, Jimin, Javier Rodriguez-Hernaez, Eric Wang, et al.. (2023). Cell-type-specific prediction of 3D chromatin organization enables high-throughput in silico genetic screening. Nature Biotechnology. 41(8). 1140–1150. 53 indexed citations
6.
Han, Cuijuan, et al.. (2023). Non-genetic mechanisms of drug resistance in acute leukemias. Trends in cancer. 10(1). 38–51. 5 indexed citations
7.
Witkowski, Matthew T., Soobeom Lee, Eric Wang, et al.. (2022). NUDT21 limits CD19 levels through alternative mRNA polyadenylation in B cell acute lymphoblastic leukemia. Nature Immunology. 23(10). 1424–1432. 26 indexed citations
8.
Haldar, Sourav, Eric Wang, Paul S. Blank, et al.. (2022). Planar aggregation of the influenza viral fusion peptide alters membrane structure and hydration, promoting poration. Nature Communications. 13(1). 7336–7336. 21 indexed citations
9.
Wang, Eric, Hua Zhou, Bettina Nadorp, et al.. (2021). Surface antigen-guided CRISPR screens identify regulators of myeloid leukemia differentiation. Cell stem cell. 28(4). 718–731.e6. 35 indexed citations
10.
Wang, Eric, Jose Mario Bello Pineda, Jessie Bourcier, et al.. (2021). Modulation of RNA Splicing Enhances Response to BCL2 Inhibition in Acute Myeloid Leukemia. Blood. 138(Supplement 1). 507–507. 2 indexed citations
11.
Wang, Eric & Iannis Aifantis. (2020). RNA Splicing and Cancer. Trends in cancer. 6(8). 631–644. 142 indexed citations
12.
Chen, Xufeng, Christina Glytsou, Hua Zhou, et al.. (2019). Targeting Mitochondrial Structure Sensitizes Acute Myeloid Leukemia to Venetoclax Treatment. Cancer Discovery. 9(7). 890–909. 214 indexed citations
13.
Shi, Junwei, Eric Wang, Joseph P. Milazzo, et al.. (2015). Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains. Nature Biotechnology. 33(6). 661–667. 500 indexed citations breakdown →
14.
Matthews, Geoffrey M., Leonie A. Cluse, Eric Wang, et al.. (2014). Abstract 5533: RNAi-mediated depletion of histone deacetylases highlights the potential for isoform-specific inhibitors in B-cell lymphoma and acute myeloid leukemia. Cancer Research. 74(19_Supplement). 5533–5533. 1 indexed citations
15.
Wang, Eric, Annette Batey, Craig A. Struble, et al.. (2013). Gestational age and maternal weight effects on fetal cell‐free DNA in maternal plasma. Prenatal Diagnosis. 33(7). 662–666. 302 indexed citations
16.
Grady, Deborah, Panayotis K. Thanos, María M. Corrada, et al.. (2013). DRD4 Genotype Predicts Longevity in Mouse and Human. Journal of Neuroscience. 33(1). 286–291. 45 indexed citations
17.
Shi, Junwei, Eric Wang, Johannes Zuber, et al.. (2012). The Polycomb complex PRC2 supports aberrant self-renewal in a mouse model of MLL-AF9;NrasG12D acute myeloid leukemia. Oncogene. 32(7). 930–938. 95 indexed citations
18.
Zuber, Johannes, Amy Rappaport, Weijun Luo, et al.. (2011). An integrated approach to dissecting oncogene addiction implicates a Myb-coordinated self-renewal program as essential for leukemia maintenance. Genes & Development. 25(15). 1628–1640. 207 indexed citations
19.
Blobel, Gerd A., Stephan Kadauke, Eric Wang, et al.. (2009). A Reconfigured Pattern of MLL Occupancy within Mitotic Chromatin Promotes Rapid Transcriptional Reactivation Following Mitotic Exit. Molecular Cell. 36(6). 970–983. 157 indexed citations
20.
Henderson, Ying C., Eric Wang, & Gary L. Clayman. (1998). Genotypic analysis of tumor suppressor genes PTEN/MMAC1 and p53 in head and neck squamous cell carcinomas. The Laryngoscope. 108(10). 1553–1556. 23 indexed citations

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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