Da-Gong Wang

1.3k total citations
11 papers, 1.1k citations indexed

About

Da-Gong Wang is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Da-Gong Wang has authored 11 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Oncology and 3 papers in Immunology. Recurrent topics in Da-Gong Wang's work include Histone Deacetylase Inhibitors Research (5 papers), Protein Degradation and Inhibitors (5 papers) and Peptidase Inhibition and Analysis (3 papers). Da-Gong Wang is often cited by papers focused on Histone Deacetylase Inhibitors Research (5 papers), Protein Degradation and Inhibitors (5 papers) and Peptidase Inhibition and Analysis (3 papers). Da-Gong Wang collaborates with scholars based in United Kingdom, United States and Switzerland. Da-Gong Wang's co-authors include Lere Bao, Kun Ping Lu, Janusz M. Sowadski, Amy Kimzey, Guido Sauter, Changgeng Qian, Xiong Cai, Cheng-Jung Lai, Guang-Xin Xu and Maria Samson and has published in prestigious journals such as Blood, Cancer and Cancer Research.

In The Last Decade

Da-Gong Wang

11 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Da-Gong Wang United Kingdom 8 910 440 248 89 78 11 1.1k
Linda Kessler United States 14 746 0.8× 352 0.8× 127 0.5× 137 1.5× 106 1.4× 38 1.1k
Mary J. C. Ludlam United States 6 673 0.7× 259 0.6× 222 0.9× 55 0.6× 48 0.6× 8 937
Michael B. Atkins United States 9 507 0.6× 507 1.2× 163 0.7× 38 0.4× 79 1.0× 14 761
Thomas B. Sundberg United States 14 765 0.8× 297 0.7× 183 0.7× 110 1.2× 63 0.8× 17 1.0k
Debra M. Hunter United States 19 538 0.6× 376 0.9× 677 2.7× 70 0.8× 65 0.8× 31 1.3k
Kristen L. Jones United States 15 492 0.5× 445 1.0× 201 0.8× 32 0.4× 139 1.8× 26 976
Silvy da Rocha Dias United Kingdom 9 656 0.7× 385 0.9× 320 1.3× 32 0.4× 33 0.4× 13 985
Susan E. Morgan-Lappe United States 11 827 0.9× 406 0.9× 171 0.7× 40 0.4× 67 0.9× 20 1.1k
Gary Borzillo United States 12 492 0.5× 169 0.4× 147 0.6× 52 0.6× 95 1.2× 24 737
Mark Fereshteh United States 9 1.0k 1.2× 445 1.0× 71 0.3× 43 0.5× 60 0.8× 18 1.4k

Countries citing papers authored by Da-Gong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Da-Gong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Da-Gong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Da-Gong Wang. A scholar is included among the top collaborators of Da-Gong 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 Da-Gong Wang. Da-Gong Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Wang, Jing, Anna Ma, Ruzanna Atoyan, et al.. (2013). CUDC-907, a Dual HDAC and PI3K Inhibitor, Potentially Targets Cancer Cells and The Microenvironment In Hematological Malignancies. Blood. 122(21). 4930–4930. 2 indexed citations
2.
Qian, Changgeng, Cheng-Jung Lai, Rudi Bao, et al.. (2012). Cancer Network Disruption by a Single Molecule Inhibitor Targeting Both Histone Deacetylase Activity and Phosphatidylinositol 3-Kinase Signaling. Clinical Cancer Research. 18(15). 4104–4113. 188 indexed citations
3.
Wang, Da-Gong, Hui Qu, Ling Yin, et al.. (2012). Abstract 3744: Antitumor activity of CUDC-907, a dual PI3K and HDAC inhibitor, in hematological cancer models. Cancer Research. 72(8_Supplement). 3744–3744. 6 indexed citations
4.
Bao, Rudi, Da-Gong Wang, Hui Qu, et al.. (2011). Abstract 2615: Antitumor activity of a dual PI3K and HDAC inhibitor in hematologic cancer models. Cancer Research. 71(8_Supplement). 2615–2615. 1 indexed citations
6.
Bao, Rudi, Cheng-Jung Lai, Hui Qu, et al.. (2009). CUDC-305, a Novel Synthetic HSP90 Inhibitor with Unique Pharmacologic Properties for Cancer Therapy. Clinical Cancer Research. 15(12). 4046–4057. 80 indexed citations
7.
Bao, Rudi, Cheng-Jung Lai, Da-Gong Wang, et al.. (2009). Targeting heat shock protein 90 with CUDC-305 overcomes erlotinib resistance in non–small cell lung cancer. Molecular Cancer Therapeutics. 8(12). 3296–3306. 47 indexed citations
8.
Bao, Lere, Amy Kimzey, Guido Sauter, et al.. (2004). Prevalent Overexpression of Prolyl Isomerase Pin1 in Human Cancers. American Journal Of Pathology. 164(5). 1727–1737. 324 indexed citations
9.
Ayala, Gustavo, Da-Gong Wang, Gerburg M. Wulf, et al.. (2003). The prolyl isomerase Pin1 is a novel prognostic marker in human prostate cancer.. PubMed. 63(19). 6244–51. 192 indexed citations
10.
Wang, Da-Gong, C.F. Johnston, James M. Sloan, & K. D. Buchanan. (1998). Expression of Bcl-2 in lung neuroendocrine tumours: comparison with p53. The Journal of Pathology. 184(3). 247–251. 36 indexed citations
11.
Wang, Da-Gong, et al.. (1996). Oncogene expression in carotid body tumors. Cancer. 77(12). 2581–2587. 20 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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