Yan C. Wang

815 total citations
9 papers, 394 citations indexed

About

Yan C. Wang is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Yan C. Wang has authored 9 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Cancer Research. Recurrent topics in Yan C. Wang's work include MicroRNA in disease regulation (3 papers), Cancer-related molecular mechanisms research (2 papers) and Chemokine receptors and signaling (2 papers). Yan C. Wang is often cited by papers focused on MicroRNA in disease regulation (3 papers), Cancer-related molecular mechanisms research (2 papers) and Chemokine receptors and signaling (2 papers). Yan C. Wang collaborates with scholars based in United States, France and Canada. Yan C. Wang's co-authors include Branimir I. Šikić, George E. Durán, Anamaria Brozović, Dejan Juric, Shalini Chaturvedi, Linda A. Snyder, Shobha Seetharam, Brian San Francisco, Kevin G. Chen and Parul Doshi and has published in prestigious journals such as Cancer Research, British Journal of Cancer and Molecular Cancer Therapeutics.

In The Last Decade

Yan C. Wang

9 papers receiving 388 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yan C. Wang United States	6	234	173	123	84	48	9	394
Ashu Shah United States	10	225 1.0×	164 0.9×	78 0.6×	92 1.1×	54 1.1×	19	401
Sylvanie Surget France	7	295 1.3×	164 0.9×	71 0.6×	46 0.5×	41 0.9×	7	433
Hiroe Nakamura Japan	12	182 0.8×	124 0.7×	113 0.9×	74 0.9×	18 0.4×	29	365
Annabelle Chow Canada	12	185 0.8×	168 1.0×	101 0.8×	88 1.0×	72 1.5×	17	398
Penny Johnson United Kingdom	9	145 0.6×	148 0.9×	69 0.6×	48 0.6×	77 1.6×	9	349
Hiroko Takenouchi Japan	10	196 0.8×	229 1.3×	132 1.1×	101 1.2×	36 0.8×	11	404
Michèle Harrison Ireland	8	211 0.9×	162 0.9×	125 1.0×	47 0.6×	64 1.3×	9	444
Ori Hassin Israel	6	307 1.3×	264 1.5×	136 1.1×	65 0.8×	75 1.6×	8	522
Shaochang Jia China	8	232 1.0×	137 0.8×	86 0.7×	106 1.3×	20 0.4×	18	400
Gudrun Hager Austria	11	171 0.7×	110 0.6×	109 0.9×	29 0.3×	44 0.9×	14	354

Countries citing papers authored by Yan C. Wang

Since Specialization

Citations

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

Fields of papers citing papers by Yan C. Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan C. Wang

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

All Works

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9 of 9 papers shown

Villalobos, Víctor M., Yan C. Wang, & Branimir I. Šikić. (2018). Reannotation and Analysis of Clinical and Chemotherapy Outcomes in the Ovarian Data Set From The Cancer Genome Atlas. JCO Clinical Cancer Informatics. 2(2). 1–16. 4 indexed citations

Durán, George E., et al.. (2017). Decreased levels of baseline and drug-induced tubulin polymerisation are hallmarks of resistance to taxanes in ovarian cancer cells and are associated with epithelial-to-mesenchymal transition. British Journal of Cancer. 116(10). 1318–1328. 42 indexed citations

Kathawala, Rishil J., David Mundy, George E. Durán, et al.. (2016). Abstract 4001: The anti-CD47 antibody Hu5F9-G4 activates macrophages and inhibits ovarian cancer xenografts, alone and in combination with chemotherapy or immunotherapy. Cancer Research. 76(14_Supplement). 4001–4001. 5 indexed citations

Brozović, Anamaria, et al.. (2015). The miR‐200 family differentially regulates sensitivity to paclitaxel and carboplatin in human ovarian carcinoma OVCAR‐3 and MES‐OV cells. Molecular Oncology. 9(8). 1678–1693. 75 indexed citations

Durán, George E., Yan C. Wang, John C. Rose, et al.. (2014). Mechanisms of Resistance to Cabazitaxel. Molecular Cancer Therapeutics. 14(1). 193–201. 78 indexed citations

Brozović, Anamaria, George E. Durán, Yan C. Wang, et al.. (2014). Enhancement of paclitaxel and carboplatin therapies by CCL2 blockade in ovarian cancers. Molecular Oncology. 8(7). 1231–1239. 97 indexed citations

Brozović, Anamaria, George E. Durán, Yan C. Wang, et al.. (2012). Abstract 817: Enhancement of paclitaxel and carboplatin therapy by CCL2 blockade in ovarian cancers. Cancer Research. 72(8_Supplement). 817–817. 1 indexed citations

Chen, Kevin G., Yan C. Wang, Marci E. Schaner, et al.. (2005). Genetic and Epigenetic Modeling of the Origins of Multidrug-Resistant Cells in a Human Sarcoma Cell Line. Cancer Research. 65(20). 9388–9397. 41 indexed citations

Wang, Yan C., Dejan Juric, Brian San Francisco, et al.. (2005). Regional activation of chromosomal arm 7q with and without gene amplification in taxane‐selected human ovarian cancer cell lines. Genes Chromosomes and Cancer. 45(4). 365–374. 51 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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