Faye Wang

817 total citations
10 papers, 601 citations indexed

About

Faye Wang is a scholar working on Molecular Biology, Infectious Diseases and Virology. According to data from OpenAlex, Faye Wang has authored 10 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Infectious Diseases and 2 papers in Virology. Recurrent topics in Faye Wang's work include HIV Research and Treatment (2 papers), HIV/AIDS drug development and treatment (2 papers) and Pluripotent Stem Cells Research (1 paper). Faye Wang is often cited by papers focused on HIV Research and Treatment (2 papers), HIV/AIDS drug development and treatment (2 papers) and Pluripotent Stem Cells Research (1 paper). Faye Wang collaborates with scholars based in United States, Netherlands and India. Faye Wang's co-authors include Catherine Soderstrom, Deborah A. Baker, Jean S. Beebe, George T. Tkalcevic, Mark W. Tengowski, Bruce D. Cohen, Antonio Gualberto, Ann Marie Rossi, James D. Moyer and Oliver Flint and has published in prestigious journals such as Blood, Clinical Cancer Research and Antimicrobial Agents and Chemotherapy.

In The Last Decade

Faye Wang

10 papers receiving 575 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Faye Wang United States 8 313 179 112 89 72 10 601
Wendong Yu United States 20 690 2.2× 50 0.3× 174 1.6× 170 1.9× 21 0.3× 41 1.3k
Weiyang Li China 19 331 1.1× 31 0.2× 155 1.4× 125 1.4× 145 2.0× 68 979
Chunmei Xie China 14 274 0.9× 26 0.1× 102 0.9× 63 0.7× 15 0.2× 27 584
Yanni Zhu United States 19 288 0.9× 82 0.5× 75 0.7× 194 2.2× 475 6.6× 40 1.1k
Swee Eng Aw Singapore 14 238 0.8× 57 0.3× 65 0.6× 138 1.6× 38 0.5× 36 687
Tujana Boldanova Switzerland 16 632 2.0× 42 0.2× 577 5.2× 335 3.8× 419 5.8× 20 1.8k
Eckart Köttgen Germany 16 426 1.4× 47 0.3× 72 0.6× 110 1.2× 12 0.2× 32 746
Min Gao China 16 160 0.5× 23 0.1× 50 0.4× 79 0.9× 153 2.1× 51 811
Chia‐Jung Liao Taiwan 18 363 1.2× 115 0.6× 209 1.9× 154 1.7× 33 0.5× 37 885
Ziwei Huang China 14 237 0.8× 32 0.2× 90 0.8× 134 1.5× 20 0.3× 34 582

Countries citing papers authored by Faye Wang

Since Specialization
Citations

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

Fields of papers citing papers by Faye Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faye Wang

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

All Works

10 of 10 papers shown
1.
Jiang, Yuying, Guangming Li, Hongyi Ge, et al.. (2022). Machine Learning and Application in Terahertz Technology: A Review on Achievements and Future Challenges. IEEE Access. 10. 53761–53776. 75 indexed citations
2.
Wang, Faye, Cindy Zhang, Jae Kwagh, et al.. (2021). TGFβ2 and TGFβ3 mediate appropriate context-dependent phenotype of rat valvular interstitial cells. iScience. 24(3). 102133–102133. 4 indexed citations
3.
4.
Wang, Faye, Jae Kwagh, Megan K. Fuller, et al.. (2016). Effects of BMS-986094, a Guanosine Nucleotide Analogue, on Mitochondrial DNA Synthesis and Function. Toxicological Sciences. 153(2). 396–408. 10 indexed citations
5.
Medine, Claire N., Baltasar Lucendo‐Villarin, Christopher Storck, et al.. (2013). Developing High-Fidelity Hepatotoxicity Models From Pluripotent Stem Cells. Stem Cells Translational Medicine. 2(7). 505–509. 103 indexed citations
6.
7.
Flint, Oliver, Jae Kwagh, Faye Wang, et al.. (2009). Tanespimycin Prevents Bortezomib Toxicity and Preserves Neuronal Morphology in Primary Rat Dorsal Root Ganglion Cultures.. Blood. 114(22). 2847–2847. 1 indexed citations
8.
Parker, Rex A., Oliver Flint, Carolina Elosua, et al.. (2005). Endoplasmic Reticulum Stress Links Dyslipidemia to Inhibition of Proteasome Activity and Glucose Transport by HIV Protease Inhibitors. Molecular Pharmacology. 67(6). 1909–1919. 86 indexed citations
9.
Cohen, Bruce D., Deborah A. Baker, Catherine Soderstrom, et al.. (2005). Combination Therapy Enhances the Inhibition of Tumor Growth with the Fully Human Anti–Type 1 Insulin-Like Growth Factor Receptor Monoclonal Antibody CP-751,871. Clinical Cancer Research. 11(5). 2063–2073. 287 indexed citations
10.
Haley, John D., David E. Smith, Richard Brennan, et al.. (2003). Identification and characterization of mechanistically distinct inducers of γ-globin transcription. Biochemical Pharmacology. 66(9). 1755–1768. 13 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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