Pingping Qu

616 citations
21 papers · 486 · h-index 10

Impact in

Papers in

    • Multiple Myeloma Research and Treatments 11
    • Protein Degradation and Inhibitors 6
    • Ubiquitin and proteasome pathways 4
    • CRISPR and Genetic Engineering 1
    • Glycosylation and Glycoproteins Research 1

Pingping Qu

21 papers receiving 472 citations

Peers

Pingping Qu
Comparison fields: 5 of 69
  • Hematology 184
  • Electrochemistry 35
  • Business and International Management 9
  • Oncology 95
  • Molecular Biology 251
Replace Zhenglan Huang with:
Zhenglan Huang China
Tatiana Pazina United States
Dagmar Orgel Germany
Jian Ge China
Ying Fei Li United States
Vicenta Trujillo-Alonso United States
Keiji Kurata Japan
Michael L. Manning United States
Madhura G. Kelkar India
Alison A. Slater Australia
Pingping Qu relative to Zhenglan Huang China Zhenglan Huang's profile →
Citations per field
00.5×2×2.9×
Zhenglan Huang · 1×
Citations per year

Countries citing papers authored by Pingping Qu

Since Specialization
Citations

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

Fields of papers citing papers by Pingping Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pingping Qu, 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 Pingping Qu Line = papers co-authored together Pingping Qu 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 201971
2 201567
3 201767
4 201158
5 201946
6 201237
7 201436
8 201829
9 201820
10 202117
11 20149
12 20217
13
Knockouts of Drought Sensitive Genes Improve Rice Grain Yield under both Drought and Well-Watered Field Conditions
20204
14 20214
15 20173
16 20083
17 20103
18 20152
19 20081
20 20161

About Pingping Qu

Pingping Qu is a scholar working on Hematology, Molecular Biology, Oncology, Cancer Research and Pathology and Forensic Medicine, having authored 21 papers that have together received 486 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (11 papers), Protein Degradation and Inhibitors (6 papers), Ubiquitin and proteasome pathways (4 papers), Electrochemical sensors and biosensors (2 papers), CRISPR and Genetic Engineering (1 paper), Glycosylation and Glycoproteins Research (1 paper), Statistical Methods in Clinical Trials (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Hematology (184 citations), Electrochemistry (35 citations), Business and International Management (9 citations), Oncology (95 citations) and Molecular Biology (251 citations). Pingping Qu has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Bart Barlogie, Joshua Epstein, John D. Shaughnessy, John Crowley, Antje Hoering, Zhihong Zhu, Frits van Rhee, Xu Wu, Yan Zeng and Haoyan Cheng. Their work appears in journals such as Blood, Clinical Cancer Research, Haematologica, Leukemia and International Journal of COPD.

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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