Haijun Tu

1.0k citations
36 papers · 760 · h-index 14

Impact in

Papers in

    • Receptor Mechanisms and Signaling 5
    • S100 Proteins and Annexins 4
    • CRISPR and Genetic Engineering 3
    • Genetics, Aging, and Longevity in Model Organisms 13

Haijun Tu

36 papers receiving 752 citations

Peers

Haijun Tu
Comparison fields: 5 of 82
  • Aging 112
  • Cellular and Molecular Neuroscience 277
  • Biological Psychiatry 29
  • Endocrine and Autonomic Systems 59
  • Developmental Neuroscience 25
Replace Chang Man Ha with:
Chang Man Ha South Korea
Adam J. Harrington United States
Hsin‐Ping Liu Taiwan
Zhenzhen Quan China
Hidenori Taru Japan
Oskar Ortiz Germany
Rafael P. Vázquez‐Manrique Spain
Guoxin Feng China
Michelle Leigh Steinhilb United States
Jessica E. Tanis United States
Haijun Tu relative to Chang Man Ha South Korea Chang Man Ha's profile →
Citations per field
00.5×
Chang Man Ha · 1×
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 201090
2 201080
3 201070
4 201565
5 200863
6 201858
7 200757
8 201452
9 202133
10 201523
11 202320
12 201217
13 202014
14 202113
15 201912
16 201912
17 202411
18 202210
19 202010
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 760 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (13 papers), Circadian rhythm and melatonin (7 papers), Neuroscience and Neuropharmacology Research (6 papers), Receptor Mechanisms and Signaling (5 papers), S100 Proteins and Annexins (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), CRISPR and Genetic Engineering (3 papers) and Neuropeptides and Animal Physiology (3 papers). The work is most often cited by research in Aging (112 citations), Cellular and Molecular Neuroscience (277 citations), Biological Psychiatry (29 citations), Endocrine and Autonomic Systems (59 citations) and Developmental Neuroscience (25 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 Maëlle Jospin. Their work appears in journals such as Frontiers in Immunology, ACS Chemical Neuroscience, The EMBO Journal, Molecular & Cellular Proteomics and Analytical Chemistry.

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.

Explore authors with similar magnitude of impact