Qingning Su

1.5k citations
32 papers · 1.3k · h-index 20

Impact in

Papers in

Qingning Su

30 papers receiving 1.3k citations

Peers

Qingning Su
Comparison fields: 5 of 112
  • Cell Biology 200
  • Cellular and Molecular Neuroscience 183
  • Pulmonary and Respiratory Medicine 294
  • Molecular Biology 554
  • Cancer Research 101
Replace Sanjay Anand with:
Sanjay Anand United States
Victor H. van Berkel United States
Artur Cieślar‐Pobuda Poland
Erik Kohlbrenner United States
Takeshi Yonezawa Japan
Patthara Kongsuphol Singapore
Yunlong Song China
Ruth M. Seeber Australia
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Citations per field
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Citations per year

Countries citing papers authored by Qingning Su

Since Specialization
Citations

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

Fields of papers citing papers by Qingning Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017130
2 2004130
3 201386
4 200084
5 200679
6 201074
7 200173
8 200967
9 201962
10 201555
11 200854
12 200952
13 201043
14 200837
15 200933
16 200733
17 200931
18 201025
19 200621
20 201421

About Qingning Su

Qingning Su is a scholar working on Pulmonary and Respiratory Medicine, Cellular and Molecular Neuroscience, Molecular Biology, Physiology and Cancer Research, having authored 32 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (7 papers), Neonatal Respiratory Health Research (6 papers), Neuroscience and Neuropharmacology Research (4 papers), Neuropeptides and Animal Physiology (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Pain Mechanisms and Treatments (3 papers), Cellular transport and secretion (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). The work is most often cited by research in Cell Biology (200 citations), Cellular and Molecular Neuroscience (183 citations), Pulmonary and Respiratory Medicine (294 citations), Molecular Biology (554 citations) and Cancer Research (101 citations). Qingning Su has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Roger A. Johns, Daniel J. Angelini, Kazuyo Yamaji-Kegan, Chunling Fan, Claudia M. Gerwin, Hunter C. Champion, JOHN T. SKINNER, Sumiko Mochida, Zu‐Hang Sheng and Carolyn L. Smith. Their work appears in journals such as American Journal of Physiology-Lung Cellular and Molecular Physiology, The Journal of Immunology, The FASEB Journal, American Journal of Respiratory Cell and Molecular Biology and PLoS ONE.

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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