Lan Ding

615 citations
24 papers · 463 · h-index 12

Impact in

Papers in

    • Renal and related cancers 2
    • RNA Research and Splicing 2
    • Receptor Mechanisms and Signaling 2
    • Genetic and Kidney Cyst Diseases 3
    • Genetic Syndromes and Imprinting 3
    • Genetic Associations and Epidemiology 3

Lan Ding

24 papers receiving 457 citations

Peers

Lan Ding
Comparison fields: 5 of 84
  • Neurology 56
  • Environmental Chemistry 58
  • Cellular and Molecular Neuroscience 89
  • Molecular Biology 282
  • Genetics 101
Replace Sérgio U. Dani with:
Sérgio U. Dani Germany
Roshan Tofighi Sweden
Shiyi Wang China
Casey O’Farrell United States
Patrick K.K. Yeung Hong Kong
Manami Oya Japan
Rima Woods United States
Ian G. Scott Finland
Denise S. Hill United States
Lan Ding relative to Sérgio U. Dani Germany Sérgio U. Dani's profile →
Citations per field
00.5×
Sérgio U. Dani · 1×
Citations per year

Countries citing papers authored by Lan Ding

Since Specialization
Citations

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

Fields of papers citing papers by Lan Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008127
2 201245
3 202244
4 200536
5 200836
6 200723
7 201322
8 202022
9 202318
10 202118
11 200214
12
Stroke and Myocardial Infarction: A Bidirectional Mendelian Randomization Study
202113
13 202410
14 20139
15 20168
16 20155
17 20242
18 20202
19
[A Chinese autosomal dominant polycystic kidney disease family probably related to PKD2 gene].
20052
20 20202

About Lan Ding

Lan Ding is a scholar working on Molecular Biology, Genetics, Epidemiology, Neurology and Surgery, having authored 24 papers that have together received 463 indexed citations. Recurring topics across this work include Genetic and Kidney Cyst Diseases (3 papers), Genetic Syndromes and Imprinting (3 papers), Genetic Associations and Epidemiology (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Renal and related cancers (2 papers), Arsenic contamination and mitigation (2 papers), RNA Research and Splicing (2 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Neurology (56 citations), Environmental Chemistry (58 citations), Cellular and Molecular Neuroscience (89 citations), Molecular Biology (282 citations) and Genetics (101 citations). Lan Ding has collaborated with scholars based in China, United States and Bahrain. Frequent co-authors include Ashok N. Hegde, Thuy K. Smith, Sudarshan C. Upadhya, Miroslav Stýblo, R. Jesse Saunders, Xinjing Liu, Zuzana Drobná, Jing Liang, Wan Zhang and Josyf C. Mychaleckyj. Their work appears in journals such as Gene, Biological Psychiatry, Cell Death Discovery, Frontiers in Psychiatry and Learning & Memory.

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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