Xinghua Long

2.8k total citations · 1 hit paper
47 papers, 2.0k citations indexed

About

Xinghua Long is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Xinghua Long has authored 47 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 15 papers in Cancer Research and 14 papers in Genetics. Recurrent topics in Xinghua Long's work include MicroRNA in disease regulation (10 papers), RNA modifications and cancer (9 papers) and Cancer-related molecular mechanisms research (8 papers). Xinghua Long is often cited by papers focused on MicroRNA in disease regulation (10 papers), RNA modifications and cancer (9 papers) and Cancer-related molecular mechanisms research (8 papers). Xinghua Long collaborates with scholars based in China, United States and South Korea. Xinghua Long's co-authors include Kenneth P. Nephew, Junli Fan, Yueting Tang, Hui Zeng, Xu Chen, Qiaoling Deng, Wei Zhang, Robert M. Bigsby, Li Zhang and Meiyun Fan and has published in prestigious journals such as JAMA, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Xinghua Long

45 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Antibodies in Infants Born to Mothers With COVID-19 Pneumonia

2020 567 citations Hui Zeng, Junli Fan et al. profile →

Peers

Xinghua Long

MB

OG

CR

ID

GENET

Jingtao Guo United States

Yogesh Singh Germany

Yoichi Kobayashi Japan

Tianmin Xu China

Jingjing Zhu China

Wencheng Ding China

Noriko Kobayashi Japan

Lili Huang China

Jingtao Guo United States

Xinghua Long

1000 ×1.3

MB

326 ×0.7

OG

189 ×0.5

CR

142 ×0.4

ID

419 ×1.3

GENET

Citations per year, relative to Xinghua Long Xinghua Long (= 1×) peers Jingtao Guo

Countries citing papers authored by Xinghua Long

Since Specialization

Citations

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

Fields of papers citing papers by Xinghua Long

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinghua Long

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Fan, Junli, et al.. (2025). RNA Modifications in Health and Disease. MedComm. 6(9). e70341–e70341. 3 indexed citations

2.

Zhang, Xuan, Yirong Li, & Xinghua Long. (2025). The interplay of mutagenesis and extracellular DNA: a new chapter in urothelial cancer research. Molecular Biomedicine. 6(1). 54–54. 1 indexed citations

3.

Li, Shiqi, et al.. (2023). N6-methyladenosine RNA modification in PD-1/PD-L1: Novel implications for immunotherapy. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1878(3). 188873–188873. 17 indexed citations

4.

Li, Shiqi, Hui Zeng, Junli Fan, et al.. (2023). Glutamine metabolism in breast cancer and possible therapeutic targets. Biochemical Pharmacology. 210. 115464–115464. 67 indexed citations

5.

Li, Shiqi, et al.. (2023). N6-methyladenosine RNA modification in nonalcoholic fatty liver disease. Trends in Endocrinology and Metabolism. 34(12). 838–848. 7 indexed citations

6.

Xu, Xianqun, et al.. (2022). APOA1 Level is Negatively Correlated with the Severity of COVID-19. SHILAP Revista de lepidopterología. 7 indexed citations

7.

Chen, Xu, Junli Fan, Peng Tang, et al.. (2021). Prevalence and Characteristics of Rheumatoid-Associated Autoantibodies in Patients with COVID-19. Journal of Inflammation Research. Volume 14. 3123–3128. 14 indexed citations

8.

Xu, Chen, et al.. (2021). The incidence of influenza in children was decreased in the first flu season after COVID-19 pandemic in Wuhan. Journal of Infection and Public Health. 14(9). 1279–1281. 8 indexed citations

9.

Zhou, Qian, et al.. (2020). Linc‐ROR promotes the progression of breast cancer and decreases the sensitivity to rapamycin through miR‐194‐3p targeting MECP2. Molecular Oncology. 14(9). 2231–2250. 40 indexed citations

10.

Guo, Juan, et al.. (2020). A novel immune-related prognostic index for predicting breast cancer overall survival. Breast Cancer. 28(2). 434–447. 8 indexed citations

11.

Ye, Peng, et al.. (2018). miR-145 overexpression triggers alteration of the whole transcriptome and inhibits breast cancer development. Biomedicine & Pharmacotherapy. 100. 72–82. 26 indexed citations

12.

Shi, Yu, et al.. (2017). Association Between MGMT Promoter Methylation and Breast Cancer: a Meta-Analysis. Cellular Physiology and Biochemistry. 42(6). 2430–2440. 21 indexed citations

13.

Zeng, Hui, et al.. (2016). Clinicopathological significance of forkhead box protein A1 in breast cancer: A meta-analysis. Experimental and Therapeutic Medicine. 11(6). 2525–2530. 10 indexed citations

14.

Fang, Cheng, Hui Zeng, Anling Li, Xianqun Xu, & Xinghua Long. (2015). Association of the pri-miR-124-1 rs531564 polymorphism with cancer risk: A meta-analysis. Molecular and Clinical Oncology. 3(4). 892–896. 10 indexed citations

15.

Zhang, Li & Xinghua Long. (2015). Association of three SNPs in TOX3 and breast cancer risk: Evidence from 97275 cases and 128686 controls. Scientific Reports. 5(1). 12773–12773. 15 indexed citations

16.

Fang, Cheng, Xuemei Wei, Xian‐Tao Zeng, et al.. (2015). Aberrant GSTP1 promoter methylation is associated with increased risk and advanced stage of breast cancer: a meta-analysis of 19 case-control studies. BMC Cancer. 15(1). 920–920. 26 indexed citations

17.

Long, Xinghua, Meiyun Fan, & Kenneth P. Nephew. (2010). Estrogen receptor-alpha-interacting cytokeratins potentiate the antiestrogenic activity of fulvestrant. Cancer Biology & Therapy. 9(5). 389–396. 11 indexed citations

18.

Long, Xinghua & Kenneth P. Nephew. (2006). Fulvestrant (ICI 182,780)-dependent Interacting Proteins Mediate Immobilization and Degradation of Estrogen Receptor-α. Journal of Biological Chemistry. 281(14). 9607–9615. 139 indexed citations

19.

Fan, Meiyun, Xinghua Long, Jason A. Bailey, et al.. (2002). The Activating Enzyme of NEDD8 Inhibits Steroid Receptor Function. Molecular Endocrinology. 16(2). 315–330. 42 indexed citations

20.

Nephew, Kenneth P., et al.. (2000). Effect of Estradiol on Estrogen Receptor Expression in Rat Uterine Cell Types1. Biology of Reproduction. 62(1). 168–177. 92 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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