Xiaoling Tong

1.5k total citations · 1 hit paper
22 papers, 948 citations indexed

About

Xiaoling Tong is a scholar working on Pulmonary and Respiratory Medicine, Cancer Research and Oncology. According to data from OpenAlex, Xiaoling Tong has authored 22 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pulmonary and Respiratory Medicine, 13 papers in Cancer Research and 9 papers in Oncology. Recurrent topics in Xiaoling Tong's work include Lung Cancer Treatments and Mutations (14 papers), Cancer Genomics and Diagnostics (13 papers) and Colorectal Cancer Treatments and Studies (7 papers). Xiaoling Tong is often cited by papers focused on Lung Cancer Treatments and Mutations (14 papers), Cancer Genomics and Diagnostics (13 papers) and Colorectal Cancer Treatments and Studies (7 papers). Xiaoling Tong collaborates with scholars based in China, United States and Canada. Xiaoling Tong's co-authors include Xue Wu, Yang Shao, Tao Jiang, Qiuxiang Ou, Hua Bao, Xiaonan Wang, Zhe Yang, Yan Wang, Caicun Zhou and Yunpeng Liu and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Scientific Reports.

In The Last Decade

Xiaoling Tong

20 papers receiving 935 citations

Hit Papers

Investigating Novel Resistance Mechanisms to Third-Genera... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoling Tong China 14 716 544 392 388 113 22 948
Yuebi Hu United States 7 739 1.0× 521 1.0× 533 1.4× 369 1.0× 158 1.4× 10 1.0k
Aleksandra Markovets United States 16 1.1k 1.6× 834 1.5× 392 1.0× 573 1.5× 127 1.1× 39 1.4k
Satoshi Yoda Japan 14 661 0.9× 490 0.9× 351 0.9× 646 1.7× 92 0.8× 27 1.1k
Mary Ann Melnick United States 9 676 0.9× 586 1.1× 261 0.7× 491 1.3× 89 0.8× 14 977
Junpei Takashima Japan 4 718 1.0× 604 1.1× 210 0.5× 483 1.2× 104 0.9× 17 946
Georgiana Kuhlmann United States 5 920 1.3× 753 1.4× 357 0.9× 500 1.3× 109 1.0× 6 1.3k
J. A. Engelman United States 12 1.0k 1.4× 834 1.5× 257 0.7× 511 1.3× 119 1.1× 24 1.3k
María Sanchez-Ronco Spain 10 731 1.0× 606 1.1× 332 0.8× 507 1.3× 89 0.8× 15 1.1k
Toshiki Takemoto Japan 15 616 0.9× 527 1.0× 161 0.4× 381 1.0× 83 0.7× 40 957
Jordi Bertrán-Alamillo Spain 14 514 0.7× 472 0.9× 299 0.8× 437 1.1× 82 0.7× 33 838

Countries citing papers authored by Xiaoling Tong

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoling Tong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoling Tong

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoling Tong. A scholar is included among the top collaborators of Xiaoling Tong 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 Xiaoling Tong. Xiaoling Tong 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.
Li, He, et al.. (2025). Bacillus velezensis RKN1111 enhances resistance against Meloidogyne incognita in Cucumis sativus . Pest Management Science. 81(6). 3403–3409. 1 indexed citations
2.
He, Liyan, et al.. (2025). Effects of microbial inoculants on soil microbial communities and enhancement of tomato yield. Journal of Microbiological Methods. 237. 107203–107203.
3.
Zhu, Chunrong, Liangjun Zhu, Yanhong Gu, et al.. (2021). Genomic Profiling Reveals the Molecular Landscape of Gastrointestinal Tract Cancers in Chinese Patients. Frontiers in Genetics. 12. 608742–608742. 9 indexed citations
4.
Tong, Xiaoling, et al.. (2021). A Clinical Study on Pulsed Low Dose Rate Radiation Therapy for Recurrent Cancers. 6(1). 4 indexed citations
5.
Cai, Lei, Yong Chen, Xiaoling Tong, et al.. (2021). The genomic landscape of young and old lung cancer patients highlights age‐dependent mutation frequencies and clinical actionability in young patients. International Journal of Cancer. 149(4). 883–892. 18 indexed citations
6.
Han, Yuchen, Li Pan, Jianying Zhang, et al.. (2020). Molecular and clinicopathological characteristics of ROS1‐rearranged non‐small‐cell lung cancers identified by next‐generation sequencing. Molecular Oncology. 14(11). 2787–2795. 26 indexed citations
8.
Qin, Yanru, Hong Jian, Xiaoling Tong, et al.. (2020). Variability of EGFR exon 20 insertions in 24 468 Chinese lung cancer patients and their divergent responses to EGFR inhibitors. Molecular Oncology. 14(8). 1695–1704. 43 indexed citations
10.
Tong, Lin, Ning Ding, Xiaoling Tong, et al.. (2019). Tumor-derived DNA from pleural effusion supernatant as a promising alternative to tumor tissue in genomic profiling of advanced lung cancer. Theranostics. 9(19). 5532–5541. 84 indexed citations
11.
Dai, Honghai, Yang Shao, Xiaoling Tong, et al.. (2019). YAP1 amplification as a prognostic factor of definitive chemoradiotherapy in nonsurgical esophageal squamous cell carcinoma. Cancer Medicine. 9(5). 1628–1637. 16 indexed citations
12.
Yang, Zhe, Nong Yang, Qiuxiang Ou, et al.. (2018). Investigating Novel Resistance Mechanisms to Third-Generation EGFR Tyrosine Kinase Inhibitor Osimertinib in Non–Small Cell Lung Cancer Patients. Clinical Cancer Research. 24(13). 3097–3107. 390 indexed citations breakdown →
13.
Xu, Yanjun, Xiaoling Tong, Junrong Yan, et al.. (2018). Short-Term Responders of Non–Small Cell Lung Cancer Patients to EGFR Tyrosine Kinase Inhibitors Display High Prevalence of TP53 Mutations and Primary Resistance Mechanisms. Translational Oncology. 11(6). 1364–1369. 20 indexed citations
14.
Lu, Hongyang, Xiaoling Tong, Fajun Xie, et al.. (2018). Targeted next generation sequencing identified clinically actionable mutations in patients with esophageal sarcomatoid carcinoma. BMC Cancer. 18(1). 251–251. 20 indexed citations
15.
16.
Zhou, Fei, Wenxiang Shen, Tao Jiang, et al.. (2017). Novel Mutations on EGFR Leu792 Potentially Correlate to Acquired Resistance to Osimertinib in Advanced NSCLC. Journal of Thoracic Oncology. 12(6). e65–e68. 74 indexed citations
17.
Shu, Yongqian, Xue Wu, Xiaoling Tong, et al.. (2017). Circulating Tumor DNA Mutation Profiling by Targeted Next Generation Sequencing Provides Guidance for Personalized Treatments in Multiple Cancer Types. Scientific Reports. 7(1). 583–583. 144 indexed citations
18.
Jiang, Junhong, Xue Wu, Xiaoling Tong, et al.. (2017). GCC2-ALK as a targetable fusion in lung adenocarcinoma and its enduring clinical responses to ALK inhibitors. Lung Cancer. 115. 5–11. 22 indexed citations
19.
Ou, Qiuxiang, Xue Wu, Hua Bao, et al.. (2017). Investigating novel resistance mechanisms to third generation EGFR TKI osimertinib in non-small cell lung cancer patients using next generation sequencing.. Journal of Clinical Oncology. 35(15_suppl). 2572–2572. 17 indexed citations
20.
Jin, Ying, Yang Shao, Xun Shi, et al.. (2016). Mutational profiling of non-small-cell lung cancer patients resistant to first-generation EGFR tyrosine kinase inhibitors using next generation sequencing. Oncotarget. 7(38). 61755–61763. 27 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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