Hanjun Guan

491 citations
12 papers · 407 · h-index 9

Impact in

Papers in

    • Signaling Pathways in Disease 2
    • S100 Proteins and Annexins 2
    • Alzheimer's disease research and treatments 6

Hanjun Guan

12 papers receiving 399 citations

Peers

Hanjun Guan
Comparison fields: 5 of 68
  • Physiology 227
  • Biological Psychiatry 18
  • Cellular and Molecular Neuroscience 129
  • Neurology 46
  • Developmental Neuroscience 20
Replace Kristina Sennvik with:
Kristina Sennvik Sweden
Arames Crameri Switzerland
Hyang-Sook Hoe United States
Christina Unger Lithner Sweden
Amanda M. DiBattista United States
Helen K. Warwick United Kingdom
Yitshak I. Francis United States
Celia Fernandez United States
Paloma Goñi‐Oliver Spain
Hanjun Guan relative to Kristina Sennvik Sweden Kristina Sennvik's profile →
Citations per field
00.5×3.7×
Kristina Sennvik · 1×
Citations per year

Countries citing papers authored by Hanjun Guan

Since Specialization
Citations

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

Fields of papers citing papers by Hanjun Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2004129
2 200868
3 200961
4 200451
5 201230
6 200721
7 201020
8
Atypical antipsychotic effects of quetiapine fumarate in animal models.
200015
9 20159
10 20081
11 20201
12 20071

About Hanjun Guan

Hanjun Guan is a scholar working on Molecular Biology, Physiology, Cellular and Molecular Neuroscience, Oncology and Pharmacology, having authored 12 papers that have together received 407 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (6 papers), Peptidase Inhibition and Analysis (5 papers), Neuroscience and Neuropharmacology Research (3 papers), Signaling Pathways in Disease (2 papers), Neuropeptides and Animal Physiology (2 papers), Protease and Inhibitor Mechanisms (2 papers), S100 Proteins and Annexins (2 papers) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Physiology (227 citations), Biological Psychiatry (18 citations), Cellular and Molecular Neuroscience (129 citations), Neurology (46 citations) and Developmental Neuroscience (20 citations). Hanjun Guan has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Louis B. Hersh, M. Paul Murphy, Yinxing Liu, Robert A. Marr, Eliezer Masliah, Inder M. Verma, Fred H. Gage, Edward Rockenstein, Mark S. Kindy and Christopher B. Eckman. Their work appears in journals such as The Journal of Urology, Molecular Therapy, Cerebral Cortex, Molecular Neurodegeneration 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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