Deyin Xing

3.2k total citations
102 papers, 2.4k citations indexed

About

Deyin Xing is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Deyin Xing has authored 102 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 23 papers in Oncology and 22 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Deyin Xing's work include Ovarian cancer diagnosis and treatment (19 papers), Uterine Myomas and Treatments (14 papers) and Gestational Trophoblastic Disease Studies (12 papers). Deyin Xing is often cited by papers focused on Ovarian cancer diagnosis and treatment (19 papers), Uterine Myomas and Treatments (14 papers) and Gestational Trophoblastic Disease Studies (12 papers). Deyin Xing collaborates with scholars based in United States, China and Czechia. Deyin Xing's co-authors include Sandra Oršulić, Dongxin Lin, Wen Tan, Xiaoping Miao, Wenfu Lu, Michael S. Goldberg, Wen‐Hann Tan, Wei Qin, Wanlong Tan and Dan-Yu Lin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and ACS Nano.

In The Last Decade

Deyin Xing

96 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deyin Xing United States 25 1.1k 861 436 432 427 102 2.4k
Antonio Palacı́n Spain 26 580 0.5× 763 0.9× 549 1.3× 312 0.7× 460 1.1× 77 2.5k
Hermann Rogatsch Austria 32 775 0.7× 573 0.7× 624 1.4× 289 0.7× 364 0.9× 80 2.6k
Robert E. Emerson United States 34 648 0.6× 575 0.7× 784 1.8× 279 0.6× 129 0.3× 73 2.4k
Michael R. Pins United States 26 870 0.8× 660 0.8× 729 1.7× 392 0.9× 149 0.3× 68 2.3k
Roman Kodet Czechia 31 1.3k 1.2× 964 1.1× 377 0.9× 316 0.7× 442 1.0× 171 3.1k
Tammy Huang United States 10 1.2k 1.1× 512 0.6× 236 0.5× 402 0.9× 414 1.0× 16 2.7k
Natália Buza United States 33 673 0.6× 1.2k 1.4× 349 0.8× 325 0.8× 258 0.6× 134 2.9k
Angela Santoro Italy 30 780 0.7× 661 0.8× 428 1.0× 465 1.1× 150 0.4× 195 2.8k
Natalja T. ter Haar Netherlands 26 700 0.6× 677 0.8× 270 0.6× 545 1.3× 384 0.9× 51 2.1k
Antonio Cavaliere Italy 22 728 0.7× 726 0.8× 348 0.8× 378 0.9× 178 0.4× 72 2.3k

Countries citing papers authored by Deyin Xing

Since Specialization
Citations

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

Fields of papers citing papers by Deyin Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deyin Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Deyin Xing. A scholar is included among the top collaborators of Deyin Xing 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 Deyin Xing. Deyin Xing 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
1.
Lim, Ling, et al.. (2024). FLT3L-induced virtual memory CD8 T cells engage the immune system against tumors. Journal of Biomedical Science. 31(1). 19–19. 5 indexed citations
2.
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4.
Xing, Deyin, et al.. (2023). Mesonephric Adenocarcinoma and Mesonephric-like Adenocarcinoma of the Urinary Tract. Modern Pathology. 36(1). 100031–100031. 4 indexed citations
5.
Lam, Brandon, John C. Lin, Claire Y.‐H. Huang, et al.. (2023). In situ vaccination via tissue-targeted cDC1 expansion enhances the immunogenicity of chemoradiation and immunotherapy. Journal of Clinical Investigation. 134(1). 12 indexed citations
6.
Chui, M. Herman, et al.. (2023). Interobserver Reproducibility in Assessing Eosinophilic Cells in Ovarian Serous Borderline Tumors to Predict BRAF Mutational Status. International Journal of Gynecological Pathology. 42(5). 472–481. 4 indexed citations
7.
Higashimoto, Tomoyasu, Christina H. Smith, John Gross, et al.. (2022). Case report of bilateral ovarian fibromas associated with de novo germline variants in PTCH1 and SMARCA4. Molecular Genetics & Genomic Medicine. 10(9). e2005–e2005. 5 indexed citations
8.
Lam, Brandon, John Lin, Louise Ferrall, et al.. (2021). Development of a Novel Mouse Model of Spontaneous High-Risk HPVE6/E7–Expressing Carcinoma in the Cervicovaginal Tract. Cancer Research. 81(17). 4560–4569. 16 indexed citations
9.
Liu, Yuehua, Russell Vang, Chien‐Fu Hung, et al.. (2020). Coexistence of Conventional Leiomyoma, Fumarate Hydratase-deficient Atypical Leiomyoma, and Perivascular Epithelioid Cell Tumor in a Uterus: A Case Study. International Journal of Gynecological Pathology. 40(2). 134–140. 4 indexed citations
10.
Xing, Deyin, Emily Adams, Jialing Huang, & Brigitte M. Ronnett. (2020). Refined diagnosis of hydatidiform moles with p57 immunohistochemistry and molecular genotyping: updated analysis of a prospective series of 2217 cases. Modern Pathology. 34(5). 961–982. 29 indexed citations
11.
Xing, Deyin & Oluwole Fadare. (2020). Molecular events in the pathogenesis of vulvar squamous cell carcinoma. Seminars in Diagnostic Pathology. 38(1). 50–61. 23 indexed citations
12.
Xing, Deyin, Gang Zheng, Aparna Pallavajjala, et al.. (2019). Lineage-Specific Alterations in Gynecologic Neoplasms with Choriocarcinomatous Differentiation: Implications for Origin and Therapeutics. Clinical Cancer Research. 25(14). 4516–4529. 22 indexed citations
13.
Howard, Robin, et al.. (2018). A Cell Line–based Immunohistochemical p53 Expression Pattern Control Panel. International Journal of Gynecological Pathology. 38(5). 449–458. 1 indexed citations
14.
Wang, Lei, Zohreh Amoozgar, Jing Huang, et al.. (2015). Decitabine Enhances Lymphocyte Migration and Function and Synergizes with CTLA-4 Blockade in a Murine Ovarian Cancer Model. Cancer Immunology Research. 3(9). 1030–1041. 132 indexed citations
15.
Righi, Elda, Satoshi Kashiwagi, J. P. Yuan, et al.. (2011). CXCL12/CXCR4 Blockade Induces Multimodal Antitumor Effects That Prolong Survival in an Immunocompetent Mouse Model of Ovarian Cancer. Cancer Research. 71(16). 5522–5534. 191 indexed citations
16.
Ibrahim, Nageatte, Lei He, Chee-Onn Leong, et al.. (2010). BRCA1-Associated Epigenetic Regulation of p73 Mediates an Effector Pathway for Chemosensitivity in Ovarian Carcinoma. Cancer Research. 70(18). 7155–7165. 41 indexed citations
17.
Goldberg, Michael S., Deyin Xing, Yin Ren, et al.. (2010). Nanoparticle-mediated delivery of siRNA targeting Parp1 extends survival of mice bearing tumors derived from Brca1-deficient ovarian cancer cells. Proceedings of the National Academy of Sciences. 108(2). 745–750. 83 indexed citations
18.
Xing, Deyin, Mai Nitta, Lei He, et al.. (2009). A Role for BRCA1 in Uterine Leiomyosarcoma. Cancer Research. 69(21). 8231–8235. 47 indexed citations
19.
Xing, Deyin & Sandra Oršulić. (2006). A Mouse Model for the Molecular Characterization of Brca1-Associated Ovarian Carcinoma. Cancer Research. 66(18). 8949–8953. 98 indexed citations
20.
Xing, Deyin & Sandra Oršulić. (2005). Modeling Resistance to Pathway-Targeted Therapy in Ovarian Cancer. Cell Cycle. 4(8). 1004–1006. 17 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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