Zikun Yang

509 total citations · 1 hit paper
9 papers, 222 citations indexed

About

Zikun Yang is a scholar working on Molecular Biology, Genetics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Zikun Yang has authored 9 papers receiving a total of 222 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Genetics and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Zikun Yang's work include Genetic Associations and Epidemiology (4 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Genetic and phenotypic traits in livestock (2 papers). Zikun Yang is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Genetic and phenotypic traits in livestock (2 papers). Zikun Yang collaborates with scholars based in United States, Peru and China. Zikun Yang's co-authors include Paul Bogdan, Shahin Nazarian, Chen Wang, Iuliana Ionita‐Laza, Annie Lee, Atlas Khan, Badri N. Vardarajan, Richard Mayeux, Krzysztof Kiryluk and Giuseppe Tosto and has published in prestigious journals such as Nature Genetics, Bioinformatics and Scientific Reports.

In The Last Decade

Zikun Yang

8 papers receiving 221 citations

Hit Papers

An in silico deep learning approach to multi-epitope vacc... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zikun Yang United States 4 168 73 53 34 29 9 222
Ariana Ghez Farrell United States 4 152 0.9× 226 3.1× 49 0.9× 26 0.8× 32 1.1× 4 304
Wenxu Jia China 5 84 0.5× 207 2.8× 42 0.8× 29 0.9× 23 0.8× 6 281
Timothy C. Yu United States 6 91 0.5× 89 1.2× 29 0.5× 21 0.6× 38 1.3× 8 186
Abdelrahman H. Abdelmoneim Sudan 5 175 1.0× 148 2.0× 62 1.2× 70 2.1× 28 1.0× 20 280
Gilles Augusto United Kingdom 7 71 0.4× 133 1.8× 15 0.3× 35 1.0× 29 1.0× 12 224
Ikenna G. Madu United States 9 155 0.9× 354 4.8× 35 0.7× 45 1.3× 55 1.9× 10 492
Mujahed I. Mustafa Sudan 8 212 1.3× 161 2.2× 82 1.5× 85 2.5× 42 1.4× 20 334
Pingping Sun China 11 363 2.2× 35 0.5× 78 1.5× 53 1.6× 32 1.1× 16 420
Jennifer M. Marshall United Kingdom 8 121 0.7× 38 0.5× 31 0.6× 59 1.7× 32 1.1× 9 272

Countries citing papers authored by Zikun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Zikun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zikun Yang

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

All Works

9 of 9 papers shown
1.
Yang, Zikun, Lu Zhang, Xinrui Jiang, et al.. (2025). Incomplete lineage sorting of segmental duplications defines the human chromosome 2 fusion site early during African great ape speciation. Cell Genomics. 6(1). 101079–101079.
2.
Yang, Zikun, Dolly Reyes‐Dumeyer, Min Suk Kang, et al.. (2025). Plasma phospho-tau217 as a predictive biomarker for Alzheimer’s disease in a large south American cohort. Alzheimer s Research & Therapy. 17(1). 1–1. 6 indexed citations
3.
Yang, Zikun, Chen Wang, Badri N. Vardarajan, et al.. (2025). Fine-mapping in admixed populations using CARMA-X, with applications to Latin American studies. The American Journal of Human Genetics. 112(5). 1215–1232. 3 indexed citations
4.
Yang, Zikun, Wenbo Qi, S. C. Chan, & H. C. Wu. (2024). MIB-Net: Balance the mutual information flow in deep learning network for multi-dimensional segmentation of COVID-19 CT images. Biomedical Signal Processing and Control. 95. 106376–106376. 1 indexed citations
5.
Yang, Zikun, Dolly Reyes‐Dumeyer, Rosa Montesinos, et al.. (2023). A benchmark study on current GWAS models in admixed populations. Briefings in Bioinformatics. 25(1). 8 indexed citations
6.
Li, Yamei, Zikun Yang, Ning Xu, et al.. (2023). Comparative transcriptome analysis between rhesus macaques (<i>Macaca mulatta</i>) and crab-eating macaques (<i>M. fascicularis</i>). 动物学研究. 45(2). 299–310. 2 indexed citations
7.
Yang, Zikun, Chen Wang, Atlas Khan, et al.. (2023). CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses. Nature Genetics. 55(6). 1057–1065. 25 indexed citations
8.
Yang, Zikun, Paul Bogdan, & Shahin Nazarian. (2021). An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study. Scientific Reports. 11(1). 3238–3238. 174 indexed citations breakdown →

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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