Run Huang

1.2k total citations
34 papers, 739 citations indexed

About

Run Huang is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Run Huang has authored 34 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cancer Research and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Run Huang's work include Cancer, Hypoxia, and Metabolism (4 papers), Reproductive Biology and Fertility (3 papers) and Ferroptosis and cancer prognosis (3 papers). Run Huang is often cited by papers focused on Cancer, Hypoxia, and Metabolism (4 papers), Reproductive Biology and Fertility (3 papers) and Ferroptosis and cancer prognosis (3 papers). Run Huang collaborates with scholars based in China, United States and Ethiopia. Run Huang's co-authors include Xiangyun Zong, Yang Yu, Sixuan Liu, Bing Xiang Yang, Xiaolin Li, Qing Yuan, Huan Chen, Jiali Yang, Xiaolin Li and Yi Li and has published in prestigious journals such as Oncogene, Clinical Cancer Research and The FASEB Journal.

In The Last Decade

Run Huang

32 papers receiving 731 citations

Peers

Run Huang
Comparison fields: 5 of 118
  • Molecular Biology 283
  • Cancer Research 218
  • Oncology 190
  • Pulmonary and Respiratory Medicine 111
  • Pathology and Forensic Medicine 71
Replace Xuesong Lu with:
Xuesong Lu China
Kristin L. Brill United States
Amal Ibrahim Egypt
Maryam Khayamzadeh Iran
Shipra Gandhi United States
Suzy Lockwood United States
Alissa Huston United States
Patriciu Achimaș-Cădariu Romania
Mohammed Imad Malki Qatar
Josep Corominas Spain
Xuesong Lu China View profile →
Citations per field, relative to Run Huang
Run Huang · 1×
Citations per year, relative to Run Huang
Run Huang · 1×

Countries citing papers authored by Run Huang

Since Specialization
Citations

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

Fields of papers citing papers by Run Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Run Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Run Huang. A scholar is included among the top collaborators of Run Huang 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 Run Huang. Run Huang 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
# Work Indexed citations
1 1
2 0
3 0
4 1
5 24
6 1
7 7
8 10
9 10
10 2
11 5
12 9
13 8
14 37
15 85
16 20
17 76
18 14
19 128
20
Investigation of source of SARS virus in laboratory animals and zoo animals
1

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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