Haiping Que

404 citations
24 papers · 323 · h-index 12

Impact in

Papers in

Haiping Que

23 papers receiving 320 citations

Peers

Haiping Que
Comparison fields: 5 of 82
  • Developmental Neuroscience 20
  • Cellular and Molecular Neuroscience 83
  • Cell Biology 61
  • Molecular Biology 181
  • Neurology 32
Replace Martin Billger with:
Martin Billger Sweden
Charles Laurent United States
Henry B. Skinner United States
Francesco Pezzini Italy
Claire Didszun Germany
Mojdeh Abbasi Australia
Youhwa Jo South Korea
Honglin Tian United States
Sherif Boulos Australia
Z Kostrouch Czechia
Haiping Que relative to Martin Billger Sweden Martin Billger's profile →
Citations per field
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Citations per year

Countries citing papers authored by Haiping Que

Since Specialization
Citations

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

Fields of papers citing papers by Haiping Que

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Haiping Que, 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 Haiping Que Line = papers co-authored together Haiping Que 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 200261
2 200538
3 200334
4 201229
5 200622
6 201115
7 201714
8 201214
9 199712
10 200912
11 200611
12
cDNA microarray analysis of spinal cord injury and regeneration related genes in rat.
200511
13 20069
14 20078
15 20167
16 20126
17 20125
18 20164
19 20134
20 20153

About Haiping Que

Haiping Que is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Cell Biology, Pathology and Forensic Medicine and Infectious Diseases, having authored 24 papers that have together received 323 indexed citations. Recurring topics across this work include Nerve injury and regeneration (6 papers), Signaling Pathways in Disease (5 papers), Endoplasmic Reticulum Stress and Disease (4 papers), Spinal Cord Injury Research (3 papers), Tuberculosis Research and Epidemiology (2 papers), Hemoglobin structure and function (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and Mycobacterium research and diagnosis (2 papers). The work is most often cited by research in Developmental Neuroscience (20 citations), Cellular and Molecular Neuroscience (83 citations), Cell Biology (61 citations), Molecular Biology (181 citations) and Neurology (32 citations). Haiping Que has collaborated with scholars based in China, Russia and United States. Frequent co-authors include Shuguang Yang, Shaojun Liu, Qinxue Ding, Shaojun Liu, Shaoxiang Xiong, Yanhong Ma, Shaojun Liu, Yong Liu, Qian Chen and Guichun Xing. Their work appears in journals such as PROTEOMICS, Cellular and Molecular Neurobiology, Journal of Neurotrauma, NeuroMolecular Medicine 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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