Pu Xia

2.8k citations
75 papers · 1.6k · h-index 21

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Cancer, Hypoxia, and Metabolism
  • Oncology top 5%
    • Cancer Cells and Metastasis

Papers in

    • Epigenetics and DNA Methylation 6
    • PI3K/AKT/mTOR signaling in cancer 5
    • Cancer Cells and Metastasis 17

Pu Xia

72 papers receiving 1.6k citations

Peers

Pu Xia
Comparison fields: 5 of 107
  • Cancer Research 392
  • Oncology 437
  • Molecular Biology 759
  • Pulmonary and Respiratory Medicine 234
  • Hepatology 57
Replace Keqiang Zhang with:
Keqiang Zhang China
Haiyong Wang China
Tao Tian China
Jieqiong Liu China
Gabriele Zoppoli Italy
Chia‐Siu Wang Taiwan
Wei‐An Chang Taiwan
Feng Zhao China
Guoxiang Cai China
Haiyong Wang China
Pu Xia relative to Keqiang Zhang China Keqiang Zhang's profile →
Citations per field
00.5×1.5×1.8×
Keqiang Zhang · 1×
Citations per year

Countries citing papers authored by Pu Xia

Since Specialization
Citations

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

Fields of papers citing papers by Pu Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pu Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pu Xia Line = papers co-authored together Pu Xia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1
PI3K/Akt/mTOR signaling pathway in cancer stem cells: from basic research to clinical application.
2015376
2 2010102
3 201075
4 201059
5 201457
6 201450
7 201038
8 201637
9 201335
10 201635
11 201032
12 201132
13 201531
14 201531
15 201129
16 201728
17 201728
18
The screening of viral risk factors in tongue and pharyngolaryngeal squamous carcinoma.
201025
19 202225
20 200921

About Pu Xia

Pu Xia is a scholar working on Molecular Biology, Oncology, Cancer Research, Pulmonary and Respiratory Medicine and Immunology, having authored 75 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (17 papers), Cancer-related molecular mechanisms research (9 papers), Cancer, Hypoxia, and Metabolism (8 papers), Epigenetics and DNA Methylation (6 papers), Ferroptosis and cancer prognosis (6 papers), Cancer Genomics and Diagnostics (6 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and MicroRNA in disease regulation (5 papers). The work is most often cited by research in Cancer Research (392 citations), Oncology (437 citations), Molecular Biology (759 citations), Pulmonary and Respiratory Medicine (234 citations) and Hepatology (57 citations). Pu Xia has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Xiaoyan Xu, Xifeng Wu, Yuanqing Ye, Hua‐chuan Zheng, Jie Lin, Jian Gu, Yasuo Takano, Da-Hua Liu, Michelle A.T. Hildebrandt and Anna Dubrovska. Their work appears in journals such as Cancer Research, Scientific Reports, Tumor Biology, International Journal of Oncology and Cancers.

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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