Hua Pan

6.5k citations
160 papers · 4.7k indexed · h-index 37

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • RNA Interference and Gene Delivery
    • Epigenetics and DNA Methylation
    • Extracellular vesicles in disease
    • Pluripotent Stem Cells Research
    • Advanced biosensing and bioanalysis techniques

Papers in

Hua Pan

150 papers receiving 4.6k citations

Peers

Hua Pan
Comparison fields: 5 of 144
  • Cancer Research 670
  • Molecular Biology 2.7k
  • Reproductive Medicine 317
  • Public Health, Environmental and Occupational Health 791
  • Immunology 546
Replace Antonio Filippini with:
Antonio Filippini Italy
Heping Xu United Kingdom
Naohiro Terada United States
Ludger Fink Germany
Satoshi Matsuda Japan
Ken–ichi Yamamura Japan
Zhugang Wang China
Sabine Hombach‐Klonisch Canada
Jean S. Campbell United States
Kwong Wai Choy Hong Kong
Hua Pan relative to Antonio Filippini Italy Antonio Filippini's profile →
Citations per field
00.5×
Antonio Filippini · 1×
Citations per year

Countries citing papers authored by Hua Pan

Since Specialization
Citations

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

Fields of papers citing papers by Hua Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20242
4 20230
5 202310
6 20227
7 20220
8 202216
9 202118
10 202153
11 202111
12 202119
13 202013
14 20195
15 20183
16 201818
17 2016117
18 20163
19 201232
20 200996

About Hua Pan

Hua Pan is a scholar working on Transplantation, Cancer Research, Neurology, Molecular Biology and Immunology, having authored 160 papers that have together received 4.7k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (22 papers), Cancer-related molecular mechanisms research (11 papers), Genetic Neurodegenerative Diseases (10 papers), MicroRNA in disease regulation (10 papers), Advanced biosensing and bioanalysis techniques (9 papers), RNA modifications and cancer (7 papers), Hereditary Neurological Disorders (7 papers) and Epigenetics and DNA Methylation (7 papers). The work is most often cited by research in Cancer Research (670 citations), Molecular Biology (2.7k citations), Reproductive Medicine (317 citations), Public Health, Environmental and Occupational Health (791 citations) and Immunology (546 citations). Hua Pan has collaborated with scholars based in United States, China and France. Frequent co-authors include Samuel A. Wickline, Richard M. Schultz, Gregory M. Lanza, Paul H. Schlesinger, Pengpeng Ma, Kirk K. Hou, Joshua L. Hood, Wenting Zhu, Christine T. N. Pham and Scott J. Bultman. Their work appears in journals such as The FASEB Journal, Scientific Reports, Developmental Biology, Proceedings of the National Academy of Sciences and Clinical Neurophysiology.

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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