Yaoshen Wang

1.3k total citations
18 papers, 167 citations indexed

About

Yaoshen Wang is a scholar working on Pediatrics, Perinatology and Child Health, Molecular Biology and Genetics. According to data from OpenAlex, Yaoshen Wang has authored 18 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Pediatrics, Perinatology and Child Health, 6 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Yaoshen Wang's work include Prenatal Screening and Diagnostics (11 papers), Parvovirus B19 Infection Studies (4 papers) and Genomic variations and chromosomal abnormalities (4 papers). Yaoshen Wang is often cited by papers focused on Prenatal Screening and Diagnostics (11 papers), Parvovirus B19 Infection Studies (4 papers) and Genomic variations and chromosomal abnormalities (4 papers). Yaoshen Wang collaborates with scholars based in China, Denmark and Botswana. Yaoshen Wang's co-authors include Asan, Junwei Sun, Zhiyu Peng, Rui Han, Chao Chen, Fengyu Guo, Lianshu Han, Wenjuan Qiu, Xiaodan Wang and Fengxia Liu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Medicine.

In The Last Decade

Yaoshen Wang

18 papers receiving 167 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yaoshen Wang China 8 84 79 50 34 19 18 167
Paulette Barahona Australia 6 74 0.9× 36 0.5× 88 1.8× 15 0.4× 10 0.5× 14 148
Tomasz Roszkowski Poland 10 140 1.7× 60 0.8× 90 1.8× 15 0.4× 17 0.9× 41 242
Elizabeth Scotchman United Kingdom 9 255 3.0× 104 1.3× 166 3.3× 18 0.5× 31 1.6× 12 335
Jorge F. Sánchez-García Spain 8 140 1.7× 117 1.5× 109 2.2× 6 0.2× 10 0.5× 13 259
Laurent Bidat France 10 262 3.1× 73 0.9× 52 1.0× 9 0.3× 93 4.9× 20 314
Núria Clusellas Spain 9 189 2.3× 100 1.3× 195 3.9× 11 0.3× 24 1.3× 14 319
Lu Meng China 6 139 1.7× 81 1.0× 153 3.1× 5 0.1× 13 0.7× 7 257
Tristan Hardy Australia 9 115 1.4× 62 0.8× 45 0.9× 4 0.1× 23 1.2× 24 220
Lissette Estrella United States 5 19 0.2× 39 0.5× 37 0.7× 12 0.4× 15 0.8× 9 238
Shoufang Qu China 8 18 0.2× 74 0.9× 30 0.6× 11 0.3× 8 0.4× 27 138

Countries citing papers authored by Yaoshen Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yaoshen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaoshen Wang

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

All Works

18 of 18 papers shown
1.
Tang, Fei, Zhonghua Wang, Yan Sun, et al.. (2024). Recurrent neural network for predicting absence of heterozygosity from low pass WGS with ultra-low depth. BMC Genomics. 25(1). 470–470. 2 indexed citations
2.
Tian, Shuai, Yaoshen Wang, Wei Zhao, et al.. (2023). Comparative study on the screening performance of a vibrating screen with and without a kneading device, based on the discrete element method. Powder Technology. 434. 119301–119301. 4 indexed citations
3.
Guo, Xueqin, Linlin Fan, Yaoshen Wang, et al.. (2023). Accuracy and depth evaluation of clinical low pass genome sequencing in the detection of mosaic aneuploidies and CNVs. BMC Medical Genomics. 16(1). 294–294. 3 indexed citations
4.
Yang, Xu, Yan Sun, Yaoshen Wang, et al.. (2023). Test development, optimization and validation of a WGS pipeline for genetic disorders. BMC Medical Genomics. 16(1). 74–74. 2 indexed citations
5.
Zhao, Sumin, Yaoshen Wang, Xiuqing Xin, et al.. (2022). Next generation sequencing is a highly reliable method to analyze exon 7 deletion of survival motor neuron 1 (SMN1) gene. Scientific Reports. 12(1). 223–223. 15 indexed citations
6.
Zeng, Fanwei, Yan Sun, Xueqin Guo, et al.. (2022). Performance characterization of PCR-free whole genome sequencing for clinical diagnosis. Medicine. 101(10). e28972–e28972. 9 indexed citations
7.
Sun, Yan, Fengxia Liu, Yaoshen Wang, et al.. (2021). Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders. BMC Medical Genomics. 14(1). 102–102. 23 indexed citations
8.
Chen, Chao, Min Chen, Yaping Zhu, et al.. (2021). Noninvasive prenatal diagnosis of monogenic disorders based on direct haplotype phasing through targeted linked-read sequencing. BMC Medical Genomics. 14(1). 244–244. 7 indexed citations
9.
Chen, Min, Chao Chen, Junwei Sun, et al.. (2020). Noninvasive prenatal diagnosis for Duchenne muscular dystrophy based on the direct haplotype phasing. Prenatal Diagnosis. 40(8). 918–924. 7 indexed citations
10.
Han, Lianshu, Chao Chen, Fengyu Guo, et al.. (2019). Noninvasive prenatal diagnosis of cobalamin C (cblC) deficiency through target region sequencing of cell‐free DNA in maternal plasma. Prenatal Diagnosis. 40(3). 324–332. 7 indexed citations
11.
Chen, Min, Chao Chen, Yuan Yuan, et al.. (2019). Haplotype-Based noninvasive prenatal diagnosis for duchenne muscular dystrophy: A pilot study in South China. European Journal of Obstetrics & Gynecology and Reproductive Biology. 240. 15–22. 3 indexed citations
12.
Ye, Jun, Chao Chen, Yuan Yuan, et al.. (2018). Haplotype-based Noninvasive Prenatal Diagnosis of Hyperphenylalaninemia through Targeted Sequencing of Maternal Plasma. Scientific Reports. 8(1). 161–161. 16 indexed citations
13.
Wang, Wenjuan, Yuan Yuan, Yaoshen Wang, et al.. (2017). A Pilot Study of Noninvasive Prenatal Diagnosis of Alpha- and Beta-Thalassemia with Target Capture Sequencing of Cell-Free Fetal DNA in Maternal Blood. Genetic Testing and Molecular Biomarkers. 21(7). 433–439. 9 indexed citations
14.
Hu, Ping, Fengchang Qiao, Yuan Yuan, et al.. (2017). Noninvasive prenatal diagnosis for X-linked disease by maternal plasma sequencing in a family of Hemophilia B. Taiwanese Journal of Obstetrics and Gynecology. 56(5). 686–690. 2 indexed citations
15.
Ma, Dingyuan, Yuan Yuan, Chunyu Luo, et al.. (2017). Noninvasive prenatal diagnosis of 21-Hydroxylase deficiency using target capture sequencing of maternal plasma DNA. Scientific Reports. 7(1). 7427–7427. 21 indexed citations
16.
Shan, Dan, Yuan Yuan, Yaoshen Wang, et al.. (2016). Non-Invasive Prenatal Diagnosis of Lethal Skeletal Dysplasia by Targeted Capture Sequencing of Maternal Plasma. PLoS ONE. 11(7). e0159355–e0159355. 14 indexed citations
17.
Lu, Sha, Ye Yuan, Yaoshen Wang, et al.. (2016). Targeted sequencing of maternal plasma for haplotype‐based non‐invasive prenatal testing of spinal muscular atrophy. Ultrasound in Obstetrics and Gynecology. 49(6). 799–802. 16 indexed citations
18.
Wang, Yaoshen, et al.. (1994). Preliminary Study on the Blood Glucose Level in the Exclusively Breastfed Newborn. Journal of Tropical Pediatrics. 40(3). 187–188. 7 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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