Haijun Tu

1.0k citations
36 papers · 720 · h-index 13

Impact in

Papers in

    • Receptor Mechanisms and Signaling 6
    • S100 Proteins and Annexins 4
    • CRISPR and Genetic Engineering 3
    • Genetics, Aging, and Longevity in Model Organisms 13

Haijun Tu

35 papers receiving 711 citations

Peers

Haijun Tu
Comparison fields: 5 of 83
  • Aging 105
  • Cellular and Molecular Neuroscience 286
  • Biological Psychiatry 34
  • Endocrine and Autonomic Systems 55
  • Developmental Neuroscience 27
Replace Adam J. Harrington with:
Adam J. Harrington United States
Arnaud Tauffenberger Canada
Zhenzhen Quan China
R.K. Somvanshi Canada
Hidenori Taru Japan
Oskar Ortiz Germany
Dylan J. Dues United States
Rafael P. Vázquez‐Manrique Spain
Francesca Farina Italy
Michelle Leigh Steinhilb United States
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Citations per field
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Citations per year

Countries citing papers authored by Haijun Tu

Since Specialization
Citations

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

Fields of papers citing papers by Haijun Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201088
2 201078
3 201070
4 201564
5 200863
6 200757
7 201857
8 201450
9 202132
10 201522
11 201217
12 202013
13 201912
14 202111
15 202311
16 201911
17 202010
18 20248
19 20227
20 20217

About Haijun Tu

Haijun Tu is a scholar working on Molecular Biology, Aging, Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems and Neurology, having authored 36 papers that have together received 720 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (13 papers), Circadian rhythm and melatonin (7 papers), Receptor Mechanisms and Signaling (6 papers), Neuroscience and Neuropharmacology Research (6 papers), S100 Proteins and Annexins (4 papers), Neuropeptides and Animal Physiology (4 papers), CRISPR and Genetic Engineering (3 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). The work is most often cited by research in Aging (105 citations), Cellular and Molecular Neuroscience (286 citations), Biological Psychiatry (34 citations), Endocrine and Autonomic Systems (55 citations) and Developmental Neuroscience (27 citations). Haijun Tu has collaborated with scholars based in China, France and United States. Frequent co-authors include Philippe Rondard, Jean‐Philippe Pin, Jianfeng Liu, Chanjuan Xu, Bérangère Pinan‐Lucarré, Jean‐Louis Bessereau, Wenhua Zhang, Eric Trinquet, Carine Monnier and Tingting Ji. Their work appears in journals such as Frontiers in Immunology, ACS Chemical Neuroscience, Molecular & Cellular Proteomics, Analytical Chemistry and The EMBO Journal.

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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