Ling Nie

1.5k citations
63 papers · 726 · h-index 15

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Genetics top 10%
    • Glioma Diagnosis and Treatment

Papers in

Ling Nie

53 papers receiving 718 citations

Peers

Ling Nie
Comparison fields: 5 of 89
  • Cancer Research 328
  • Genetics 93
  • Molecular Biology 445
  • Pulmonary and Respiratory Medicine 209
  • Structural Biology 5
Replace Raul Perret with:
Raul Perret France
Gabriella Gaudioso Italy
Makoto Shibuya Japan
A Fornari Italy
Katalin Dezső Hungary
Zheng Xu China
Peter Libby United States
Ye Zhou China
Ling Nie relative to Raul Perret France Raul Perret's profile →
Citations per field
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Raul Perret · 1×
Citations per year

Countries citing papers authored by Ling Nie

Since Specialization
Citations

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

Fields of papers citing papers by Ling Nie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017130
2 2010121
3 202240
4
SOX9 was involved in TKIs resistance in renal cell carcinoma via Raf/MEK/ERK signaling pathway.
201527
5 201626
6 201323
7 201121
8 201921
9 201819
10 201918
11 202017
12 201217
13 202017
14 202316
15 201814
16 201513
17 201513
18 202110
19 202110
20 202210

About Ling Nie

Ling Nie is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Cancer Research, Genetics and Cardiology and Cardiovascular Medicine, having authored 63 papers that have together received 726 indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (12 papers), Cancer-related molecular mechanisms research (9 papers), Prostate Cancer Diagnosis and Treatment (7 papers), Renal cell carcinoma treatment (6 papers), Glioma Diagnosis and Treatment (6 papers), Cancer, Lipids, and Metabolism (5 papers), MicroRNA in disease regulation (5 papers) and Renal and related cancers (5 papers). The work is most often cited by research in Cancer Research (328 citations), Genetics (93 citations), Molecular Biology (445 citations), Pulmonary and Respiratory Medicine (209 citations) and Structural Biology (5 citations). Ling Nie has collaborated with scholars based in China, Switzerland and United Kingdom. Frequent co-authors include Qiao Zhou, Miao Xu, Xueqin Chen, Ni Chen, Mengni Zhang, Ni Chen, Hao Zeng, Xinglan Li, Jing Gong and Xueqin Chen. Their work appears in journals such as The Prostate, Journal of Clinical Pathology, Neuropathology, Annals of Oncology and Scientific Reports.

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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