Runxia Gu

873 citations
50 papers · 436 · h-index 10

Impact in

Papers in

    • Acute Myeloid Leukemia Research 15
    • Chronic Myeloid Leukemia Treatments 9
    • Protein Degradation and Inhibitors 4
    • Epigenetics and DNA Methylation 3

Runxia Gu

39 papers receiving 424 citations

Peers

Runxia Gu
Comparison fields: 5 of 78
  • Hematology 56
  • Oncology 100
  • Immunology 77
  • Nutrition and Dietetics 49
  • Cancer Research 42
Replace Snehalata A. Pawar with:
Snehalata A. Pawar United States
Rubén Fernández‐Rodríguez Spain
Xiao‐Yan Bai China
Olivier Cerles France
Elaine Beem United States
Anna Brózik Hungary
Matityahu Shaklai Israel
Tomomi Hashidate‐Yoshida Japan
José María Ros Rodríguez United States
Domenico Mastrangelo Italy
Runxia Gu relative to Snehalata A. Pawar United States Snehalata A. Pawar's profile →
Citations per field
00.5×
Snehalata A. Pawar · 1×
Citations per year

Countries citing papers authored by Runxia Gu

Since Specialization
Citations

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

Fields of papers citing papers by Runxia Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Runxia Gu, 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 Runxia Gu Line = papers co-authored together Runxia Gu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013104
2 201368
3 201829
4 201326
5 202026
6 201725
7 201518
8 201214
9 201513
10
TLR3 correlated with cervical lymph node metastasis in patients with papillary thyroid cancer.
201412
11 20218
12 20238
13 20247
14 20246
15 20246
16 20236
17 20176
18 20216
19 20245
20 20245

About Runxia Gu

Runxia Gu is a scholar working on Hematology, Molecular Biology, Oncology, Public Health, Environmental and Occupational Health and Pathology and Forensic Medicine, having authored 50 papers that have together received 436 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (15 papers), CAR-T cell therapy research (10 papers), Acute Lymphoblastic Leukemia research (10 papers), Chronic Myeloid Leukemia Treatments (9 papers), Protein Degradation and Inhibitors (4 papers), Immune Cell Function and Interaction (3 papers), Epigenetics and DNA Methylation (3 papers) and Cancer Mechanisms and Therapy (3 papers). The work is most often cited by research in Hematology (56 citations), Oncology (100 citations), Immunology (77 citations), Nutrition and Dietetics (49 citations) and Cancer Research (42 citations). Runxia Gu has collaborated with scholars based in China and United States. Frequent co-authors include Hui Wei, Dapeng Li, Xue Yang, Gang Wu, Wenqian Cai, Pingwei Xu, Junli Liu, Ke Tang, Longqiang Wang and Yi Zhang. Their work appears in journals such as Blood, Molecular Oncology, Biochemical and Biophysical Research Communications, Leukemia and PLoS ONE.

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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