Xingyi Guo

7.5k total citations
99 papers, 2.4k citations indexed

About

Xingyi Guo is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Xingyi Guo has authored 99 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 34 papers in Genetics and 28 papers in Cancer Research. Recurrent topics in Xingyi Guo's work include Genetic Associations and Epidemiology (21 papers), Cancer Genomics and Diagnostics (14 papers) and RNA modifications and cancer (11 papers). Xingyi Guo is often cited by papers focused on Genetic Associations and Epidemiology (21 papers), Cancer Genomics and Diagnostics (14 papers) and RNA modifications and cancer (11 papers). Xingyi Guo collaborates with scholars based in United States, China and Canada. Xingyi Guo's co-authors include Deyou Zheng, Wei Zheng, Elaine Fuchs, Longjiang Fan, Qiuyin Cai, Wen‐Hui Lien, Jiandong Bao, Lisa Polak, Xiao‐Ou Shu and Jirong Long and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Xingyi Guo

95 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xingyi Guo United States 27 1.3k 440 379 284 271 99 2.4k
Alessandra Fierabracci Italy 31 1.3k 1.0× 441 1.0× 683 1.8× 60 0.2× 142 0.5× 111 3.3k
Yosuke Kawai Japan 24 1.0k 0.8× 187 0.4× 359 0.9× 142 0.5× 98 0.4× 116 2.0k
Hirofumi Nagai Japan 22 527 0.4× 79 0.2× 174 0.5× 149 0.5× 505 1.9× 60 2.1k
Hiroki Nakayama Japan 29 905 0.7× 130 0.3× 320 0.8× 270 1.0× 203 0.7× 111 2.5k
Ian Roberts United Kingdom 24 1.2k 0.9× 522 1.2× 303 0.8× 83 0.3× 187 0.7× 44 2.0k
Kayoko Higuchi Japan 25 791 0.6× 165 0.4× 136 0.4× 68 0.2× 248 0.9× 117 2.2k
Silvia D’Alessio Italy 25 796 0.6× 528 1.2× 327 0.9× 32 0.1× 167 0.6× 49 2.1k
Baolin Wang China 29 3.5k 2.6× 228 0.5× 1.4k 3.7× 42 0.1× 296 1.1× 78 4.4k
Igor Dozmorov United States 30 1.1k 0.8× 298 0.7× 210 0.6× 61 0.2× 139 0.5× 97 2.7k
Ken Taniguchi Japan 23 1.4k 1.0× 270 0.6× 366 1.0× 51 0.2× 298 1.1× 67 3.5k

Countries citing papers authored by Xingyi Guo

Since Specialization
Citations

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

Fields of papers citing papers by Xingyi Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingyi Guo

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

All Works

20 of 20 papers shown
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Wang, Cong, Hui Cai, Qiuyin Cai, et al.. (2024). Circulating microRNAs in association with pancreatic cancer risk within 5 years. International Journal of Cancer. 155(3). 519–531. 4 indexed citations
4.
Park, Kyong Hwa, Yeul Hong Kim, K. Jason, et al.. (2024). Large-Scale Cancer Genomic Analysis Reveals Significant Disparities between Microsatellite Instability and Tumor Mutational Burden. Cancer Epidemiology Biomarkers & Prevention. 33(5). 712–720. 1 indexed citations
5.
Jia, Guochong, Yaohua Yang, Jie Ping, et al.. (2023). Identification of target proteins for breast cancer genetic risk loci and blood risk biomarkers in a large study by integrating genomic and proteomic data. International Journal of Cancer. 152(11). 2314–2320. 5 indexed citations
6.
Yang, Yaohua, Guochong Jia, Jie Ping, et al.. (2023). Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants. British Journal of Cancer. 129(9). 1510–1515. 6 indexed citations
7.
Kim, Jung Sun, Hwa Jung Sung, Yu‐Wei Chen, et al.. (2022). Polygenic Risk Scores Associated with Tumor Immune Infiltration in Common Cancers. Cancers. 14(22). 5571–5571. 3 indexed citations
8.
Holowatyj, Andreana N., Wanqing Wen, Timothy E. Gibbs, et al.. (2022). Racial/Ethnic and Sex Differences in Somatic Cancer Gene Mutations among Patients with Early-Onset Colorectal Cancer. Cancer Discovery. 13(3). 570–579. 30 indexed citations
9.
Postoak, J. Luke, Wenqiang Song, Guan Yang, et al.. (2022). Thymic epithelial cells require lipid kinase Vps34 for CD4 but not CD8 T cell selection. The Journal of Experimental Medicine. 219(10). 11 indexed citations
10.
Lü, Mei, et al.. (2022). Conjugation of the Fn14 Ligand to a SMAC Mimetic Selectively Suppresses Experimental Squamous Cell Carcinoma in Mice. Journal of Investigative Dermatology. 143(2). 242–253.e6. 2 indexed citations
11.
Guo, Xingyi, Jie Ping, Wanqing Wen, et al.. (2022). Evaluating breast cancer predisposition genes in women of African ancestry. Genetics in Medicine. 24(7). 1468–1475. 6 indexed citations
12.
Cai, Qiuyin, et al.. (2022). The putative oncogenic role of WDTC1 in colorectal cancer. Carcinogenesis. 43(6). 594–600. 4 indexed citations
13.
Cao, Chen, Devin Kwok, Qing Li, et al.. (2021). Disentangling genetic feature selection and aggregation in transcriptome-wide association studies. Genetics. 220(2). 19 indexed citations
14.
Ping, Jie, Xingyi Guo, Fei Ye, et al.. (2020). Differences in gene-expression profiles in breast cancer between African and European-ancestry women. Carcinogenesis. 41(7). 887–893. 9 indexed citations
15.
Campbell, Benjamin R., Zhishan Chen, Daniel L. Faden, et al.. (2020). The mutational landscape of early‐ and typical‐onset oral tongue squamous cell carcinoma. Cancer. 127(4). 544–553. 30 indexed citations
16.
Wu, Lang, Jifeng Wang, Qiuyin Cai, et al.. (2019). Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants. Cancer Research. 79(13). 3192–3204. 37 indexed citations
17.
Wu, Lang, Xiang Shu, Jiandong Bao, et al.. (2019). Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk. Cancer Research. 79(18). 4592–4598. 16 indexed citations
18.
Guo, Xingyi, Jirong Long, Zhishan Chen, et al.. (2019). Discovery of rare coding variants in OGDHL and BRCA2 in relation to breast cancer risk in Chinese women. International Journal of Cancer. 146(8). 2175–2181. 8 indexed citations
19.
Wang, Shuyang, Alicia Beeghly‐Fadiel, Qiuyin Cai, et al.. (2018). Gene expression in triple-negative breast cancer in relation to survival. Breast Cancer Research and Treatment. 171(1). 199–207. 33 indexed citations
20.
Keyes, Brice E., Jeremy P. Segal, Evan Heller, et al.. (2013). Nfatc1 orchestrates aging in hair follicle stem cells. Proceedings of the National Academy of Sciences. 110(51). E4950–9. 133 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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