Xiaoran Ding

577 citations
21 papers · 494 · h-index 12

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Hepatology top 10%
    • Hepatitis C virus research

Papers in

    • RNA Interference and Gene Delivery 6
    • Molecular Biology Techniques and Applications 3
    • Hepatitis B Virus Studies 8

Xiaoran Ding

20 papers receiving 487 citations

Peers

Xiaoran Ding
Comparison fields: 5 of 82
  • Cancer Research 154
  • Hepatology 76
  • Immunology 115
  • Epidemiology 181
  • Molecular Biology 254
Replace Gaofeng Lu with:
Gaofeng Lu China
Stephanie T. Chan United States
Jesse Donovan United States
Xue Hu China
Shipin Wu China
Wensong Jin China
Xiaoang Yang China
Ching‐Shu Suen Taiwan
Mengdie Fang China
Dachuan Cai China
Xiaoran Ding relative to Gaofeng Lu China Gaofeng Lu's profile →
Citations per field
00.5×1.5×2.2×
Gaofeng Lu · 1×
Citations per year

Countries citing papers authored by Xiaoran Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoran Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012101
2 201293
3 200783
4 200524
5 201224
6 200723
7 201019
8 201116
9 201815
10 201612
11 200612
12 201311
13 201711
14 20169
15 20229
16 20178
17 20128
18 20087
19 20226
20 20243

About Xiaoran Ding

Xiaoran Ding is a scholar working on Molecular Biology, Epidemiology, Immunology, Hepatology and Cancer Research, having authored 21 papers that have together received 494 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (8 papers), RNA Interference and Gene Delivery (6 papers), MicroRNA in disease regulation (3 papers), Hepatitis C virus research (3 papers), Molecular Biology Techniques and Applications (3 papers), Immunotherapy and Immune Responses (3 papers), Forensic and Genetic Research (2 papers) and HIV Research and Treatment (2 papers). The work is most often cited by research in Cancer Research (154 citations), Hepatology (76 citations), Immunology (115 citations), Epidemiology (181 citations) and Molecular Biology (254 citations). Xiaoran Ding has collaborated with scholars based in China and United States. Frequent co-authors include Shengqi Wang, Jing Yang, Xuejun Wang, Zhe Zhou, Xiaochen Bo, Ying Li, Jing Yang, Xiujuan Zhang, Wei Hu and Hongshan Chen. Their work appears in journals such as Antiviral Research, Archives of Virology, Electrophoresis, PLoS ONE and The Pharmacogenomics Journal.

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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