Xinghua Shi

10.9k total citations
78 papers, 1.7k citations indexed

About

Xinghua Shi is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Xinghua Shi has authored 78 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 24 papers in Artificial Intelligence and 19 papers in Genetics. Recurrent topics in Xinghua Shi's work include Gene expression and cancer classification (19 papers), Privacy-Preserving Technologies in Data (10 papers) and Genetic Associations and Epidemiology (9 papers). Xinghua Shi is often cited by papers focused on Gene expression and cancer classification (19 papers), Privacy-Preserving Technologies in Data (10 papers) and Genetic Associations and Epidemiology (9 papers). Xinghua Shi collaborates with scholars based in United States, China and Canada. Xinghua Shi's co-authors include Yu Wang, Ying Zhu, Bin Xu, Timothée Lionnet, Wulan Deng, Robert H. Singer, Robert Tjian, Junjie Chen, Xintao Wu and Andrew Quitadamo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

In The Last Decade

Xinghua Shi

74 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xinghua Shi United States	22	745	346	290	225	224	78	1.7k
Nam V. Nguyen United States	14	564 0.8×	301 0.9×	336 1.2×	165 0.7×	312 1.4×	51	1.6k
Francisco Tirado Spain	19	825 1.1×	197 0.6×	188 0.6×	201 0.9×	98 0.4×	97	2.0k
Chun Chen China	23	631 0.8×	272 0.8×	176 0.6×	127 0.6×	91 0.4×	75	1.8k
Edward Suh United States	18	649 0.9×	148 0.4×	299 1.0×	92 0.4×	148 0.7×	29	1.6k
Akihiko Konagaya Japan	25	1.6k 2.1×	177 0.5×	296 1.0×	72 0.3×	147 0.7×	136	2.4k
Mehmet Koyutürk United States	30	1.7k 2.3×	125 0.4×	307 1.1×	180 0.8×	245 1.1×	122	2.7k
Michael D. Linderman United States	22	927 1.2×	318 0.9×	156 0.5×	167 0.7×	351 1.6×	45	2.4k
Ivan Merelli Italy	22	1.3k 1.7×	149 0.4×	93 0.3×	128 0.6×	407 1.8×	144	2.0k
Mario Rosario Guarracino Italy	21	564 0.8×	96 0.3×	186 0.6×	117 0.5×	117 0.5×	105	1.4k
Byunghan Lee South Korea	12	791 1.1×	86 0.2×	346 1.2×	190 0.8×	56 0.3×	22	1.6k

Countries citing papers authored by Xinghua Shi

Since Specialization

Citations

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

Fields of papers citing papers by Xinghua Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinghua Shi

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

All Works

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20 of 20 papers shown

Jamialahmadi, Oveis, Raquel Dias, Junjie Chen, et al.. (2025). STICI: Split-Transformer with integrated convolutions for genotype imputation. Nature Communications. 16(1). 1218–1218. 1 indexed citations

Zhang, Kai, et al.. (2025). Enhancing fairness in disease prediction by optimizing multiple domain adversarial networks. PLOS Digital Health. 4(5). e0000830–e0000830. 1 indexed citations

Ye, Kejiang, et al.. (2024). Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds. IEEE Transactions on Parallel and Distributed Systems. 35(8). 1456–1468. 6 indexed citations

Saaoud, Fatma, Yifan Lu, Keman Xu, et al.. (2024). Innate immunity of vascular smooth muscle cells contributes to two-wave inflammation in atherosclerosis, twin-peak inflammation in aortic aneurysms and trans-differentiation potential into 25 cell types. Frontiers in Immunology. 14. 1348238–1348238. 20 indexed citations

Chen, Junjie, Jiahao Li, Bin Li, et al.. (2024). Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11338–11345.

Shi, Xinghua, et al.. (2023). IGFBP7 Fuels the Glycolytic Metabolism in B-Cell Precursor Acute Lymphoblastic Leukemia by Sustaining Activation of the IGF1R–Akt–GLUT1 Axis. International Journal of Molecular Sciences. 24(11). 9679–9679. 7 indexed citations

Shi, Xinghua, et al.. (2022). Offspring GAN augments biased human genomic data. 1–10. 4 indexed citations

Shi, Xinghua, et al.. (2022). Participant Selection for Hierarchical Federated Learning in Edge Clouds. 1–8. 9 indexed citations

Song, Meng, Jonathan Greenbaum, Joseph Luttrell, et al.. (2022). An autoencoder-based deep learning method for genotype imputation. Frontiers in Artificial Intelligence. 5. 1028978–1028978. 8 indexed citations

10.

Zheng, Bo, Chong Li, Shrabani Basu, et al.. (2021). The RNA structurome in the asexual blood stages of malaria pathogen plasmodium falciparum. RNA Biology. 18(12). 2480–2497. 5 indexed citations

11.

Yu, Gang, Chao Xu, Xinghua Shi, et al.. (2021). Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images. Nature Communications. 12(1). 6311–6311. 78 indexed citations

12.

Chen, Junjie, Hui Wang, & Xinghua Shi. (2020). Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data. PubMed. 26. 26–37. 32 indexed citations

13.

Chen, Junjie & Xinghua Shi. (2019). Sparse Convolutional Denoising Autoencoders for Genotype Imputation. Genes. 10(9). 652–652. 22 indexed citations

14.

Shi, Xinghua. (2019). eQTL Analysis. Methods in molecular biology. 6 indexed citations

15.

Wang, Weichao, Xinghua Shi, & Tuanfa Qin. (2018). Encryption-free Authentication and Integrity Protection in Body Area Networks through Physical Unclonable Functions. Smart Health. 12. 66–81. 20 indexed citations

16.

Lin, Maoxuan, et al.. (2017). Effects of short indels on protein structure and function in human genomes. Scientific Reports. 7(1). 9313–9313. 61 indexed citations

17.

Zhang, Lu, et al.. (2016). Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. 529–532. 6 indexed citations

18.

Wang, Zhiyong, et al.. (2015). A Sparse Learning Framework for Joint Effect Analysis of Copy Number Variants. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 14(5). 1013–1027. 1 indexed citations

19.

Wang, Zhiyong, Jinbo Xu, & Xinghua Shi. (2014). CNVnet. 128–137. 1 indexed citations

20.

Shi, Xinghua & Yimin Wei. (2012). A sharp version of Bauer–Fike’s theorem. Journal of Computational and Applied Mathematics. 236(13). 3218–3227. 8 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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