Qing Lu

2.4k citations
48 papers · 1.9k · h-index 24

Impact in

Papers in

Qing Lu

46 papers receiving 1.9k citations

Peers

Qing Lu
Comparison fields: 5 of 98
  • Developmental Neuroscience 140
  • Endocrinology, Diabetes and Metabolism 463
  • Reproductive Medicine 140
  • Cell Biology 264
  • Genetics 385
Replace Masayuki Tanemoto with:
Masayuki Tanemoto Japan
Xiaodong Fu China
Richard S. Haber United States
Hiroto Furuta Japan
Zohre German United States
Melissa K. Thomas United States
Robert G. Tsushima Canada
David A. Jacobson United States
Junji Ishida Japan
Masatoshi Kikuchi Japan
Qing Lu relative to Masayuki Tanemoto Japan Masayuki Tanemoto's profile →
Citations per field
00.5×2.9×
Masayuki Tanemoto · 1×
Citations per year

Countries citing papers authored by Qing Lu

Since Specialization
Citations

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

Fields of papers citing papers by Qing Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004217
2 2006152
3 2003104
4 199395
5 201187
6 201487
7 201280
8 201472
9 199471
10 201865
11 201961
12 201358
13 200357
14 200152
15 201950
16 200247
17 200246
18 199946
19 201245
20 201642

About Qing Lu

Qing Lu is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Molecular Biology, Surgery and Oncology, having authored 48 papers that have together received 1.9k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (10 papers), Hormonal Regulation and Hypertension (8 papers), Microtubule and mitosis dynamics (5 papers), Chronic Myeloid Leukemia Treatments (5 papers), Reproductive Biology and Fertility (5 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers), Cytokine Signaling Pathways and Interactions (4 papers) and Sperm and Testicular Function (3 papers). The work is most often cited by research in Developmental Neuroscience (140 citations), Endocrinology, Diabetes and Metabolism (463 citations), Reproductive Medicine (140 citations), Cell Biology (264 citations) and Genetics (385 citations). Qing Lu has collaborated with scholars based in United States, China and Brazil. Frequent co-authors include Richard H. Karas, Richard F. Ludueña, Wendy Baur, Iris Z. Jaffe, Michael E. Mendelsohn, Howard K. Surks, David C. Pallas, Kazutaka Ueda, Qing‐Yuan Sun and Mark Aronovitz. Their work appears in journals such as Arteriosclerosis Thrombosis and Vascular Biology, Hypertension, Biology of Reproduction, Endocrinology 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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