Yexun Wang

719 total citations
10 papers, 402 citations indexed

About

Yexun Wang is a scholar working on Molecular Biology, Cancer Research and Bioengineering. According to data from OpenAlex, Yexun Wang has authored 10 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Cancer Research and 2 papers in Bioengineering. Recurrent topics in Yexun Wang's work include Genomics and Phylogenetic Studies (5 papers), Molecular Biology Techniques and Applications (5 papers) and Cancer Genomics and Diagnostics (4 papers). Yexun Wang is often cited by papers focused on Genomics and Phylogenetic Studies (5 papers), Molecular Biology Techniques and Applications (5 papers) and Cancer Genomics and Diagnostics (4 papers). Yexun Wang collaborates with scholars based in China, Cyprus and United States. Yexun Wang's co-authors include John DiCarlo, Peng Quan, Ravi Vijaya Satya, Chang Xu, Zhong Wu, Huilei Xu, Mohammad Ranjbar, Xiujing Gu, Peng Quan and William S. Branham and has published in prestigious journals such as Bioinformatics, Cancer Research and Scientific Reports.

In The Last Decade

Yexun Wang

10 papers receiving 389 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yexun Wang China	6	239	238	95	72	62	10	402
Erik N. Bergstrom United States	9	248 1.0×	314 1.3×	70 0.7×	111 1.5×	56 0.9×	14	463
Frank McCaughan United Kingdom	12	209 0.9×	303 1.3×	42 0.4×	139 1.9×	51 0.8×	18	511
Yussanne Ma Canada	12	179 0.7×	260 1.1×	51 0.5×	85 1.2×	65 1.0×	20	425
Michelle Dietzen United Kingdom	6	224 0.9×	192 0.8×	59 0.6×	137 1.9×	46 0.7×	8	382
Dayna M. Oschwald United States	6	189 0.8×	149 0.6×	55 0.6×	170 2.4×	144 2.3×	8	412
Nathalie Forey France	11	159 0.7×	223 0.9×	144 1.5×	66 0.9×	54 0.9×	15	409
Mia Petljak United States	7	279 1.2×	408 1.7×	99 1.0×	169 2.3×	65 1.0×	9	590
Alberto Cedro‐Tanda Mexico	11	214 0.9×	238 1.0×	34 0.4×	79 1.1×	22 0.4×	24	395
Karl-Henning Kalland Norway	10	149 0.6×	247 1.0×	40 0.4×	70 1.0×	20 0.3×	13	402
Ann C. Burgess United States	8	126 0.5×	312 1.3×	239 2.5×	157 2.2×	68 1.1×	15	595

Countries citing papers authored by Yexun Wang

Since Specialization

Citations

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

Fields of papers citing papers by Yexun Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yexun Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Quan, Peng, et al.. (2019). Targeted Single Primer Enrichment Sequencing with Single End Duplex-UMI. Scientific Reports. 9(1). 4810–4810. 24 indexed citations

2.

Xu, Chang, Xiujing Gu, Zhong Wu, et al.. (2018). smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers. Bioinformatics. 35(8). 1299–1309. 70 indexed citations

3.

Xu, Chang, Mohammad Ranjbar, Zhong Wu, John DiCarlo, & Yexun Wang. (2017). Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller. BMC Genomics. 18(1). 5–5. 78 indexed citations

4.

Quan, Peng, et al.. (2015). Reducing amplification artifacts in high multiplex amplicon sequencing by using molecular barcodes. BMC Genomics. 16(1). 589–589. 86 indexed citations

5.

Quan, Peng, et al.. (2015). Abstract 4879: Reducing amplification artifacts in highly multiplex amplicon sequencing by using molecular barcodes. Cancer Research. 75(15_Supplement). 4879–4879. 1 indexed citations

6.

Xu, Huilei, John DiCarlo, Ravi Vijaya Satya, Peng Quan, & Yexun Wang. (2014). Comparison of somatic mutation calling methods in amplicon and whole exome sequence data. BMC Genomics. 15(1). 244–244. 105 indexed citations

7.

Long, Samuel, Min You, Liang Wang, et al.. (2011). Abstract 4863: Pathway-focused cancer mutation profiling with somatic mutation PCR arrays. Cancer Research. 71(8_Supplement). 4863–4863. 1 indexed citations

8.

Li, Zhiguang, William S. Branham, Stacey L. Dial, et al.. (2010). Genomic analysis of microRNA time-course expression in liver of mice treated with genotoxic carcinogen N-ethyl-N-nitrosourea. BMC Genomics. 11(1). 609–609. 34 indexed citations

9.

Wang, Zhenghao & Yexun Wang. (1998). A digital simulation study of two-dimensional convection diffusion for channel electrode. Science China Chemistry. 41(2). 187–193. 2 indexed citations

10.

Wang, Zhenghao & Yexun Wang. (1998). A digital simulation study of two-dimensional convection diffusion for channel electrode. Science in China Series B Chemistry. 41(2). 187–193. 1 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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