Hongjun Fu

5.2k citations
69 papers · 3.4k indexed · 3 hit papers · h-index 28

Impact in

Papers in

Hongjun Fu

69 papers receiving 3.3k citations

Hit Papers

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses 2021 · 250 citations
2502016202620192022100200300400500

Peers

Hongjun Fu
Comparison fields: 5 of 141
  • Neurology 788
  • Biological Psychiatry 147
  • Physiology 1.4k
  • Cellular and Molecular Neuroscience 766
  • Developmental Neuroscience 166
Replace Manuela Polydoro with:
Manuela Polydoro United States
Lee‐Way Jin United States
Marcello D’Amelio Italy
Jiankun Cui United States
Mei Yue United States
Erika Maus United States
Amaya García-Muñoz Ireland
Véronique Blanchard Germany
Per Nilsson Sweden
Justin M. Long United States
Hongjun Fu relative to Manuela Polydoro United States Manuela Polydoro's profile →
Citations per field
00.5×
Manuela Polydoro · 1×
Citations per year

Countries citing papers authored by Hongjun Fu

Since Specialization
Citations

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

Fields of papers citing papers by Hongjun Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202410
2 20245
3 20242
4 202422
5 202316
6 202319
7 2022115
8 20223
9
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses
Hit paper breakdown →
2021250
10 202117
11 202018
12 202023
13
Selective vulnerability in neurodegenerative diseases
Hit paper breakdown →
2018354
14 2018167
15
Neuronal activity enhances tau propagation and tau pathology in vivo
Hit paper breakdown →
2016574
16 201615
17 201417
18 2013145
19 201029
20 200715

About Hongjun Fu

Hongjun Fu is a scholar working on Neurology, Process Chemistry and Technology, Physiology, Cellular and Molecular Neuroscience and Pharmacology, having authored 69 papers that have together received 3.4k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (26 papers), Neuroinflammation and Neurodegeneration Mechanisms (14 papers), Neuroscience and Neuropharmacology Research (14 papers), Cholinesterase and Neurodegenerative Diseases (12 papers), Single-cell and spatial transcriptomics (6 papers), Heavy Metal Exposure and Toxicity (5 papers), Nicotinic Acetylcholine Receptors Study (5 papers) and Trace Elements in Health (4 papers). The work is most often cited by research in Neurology (788 citations), Biological Psychiatry (147 citations), Physiology (1.4k citations), Cellular and Molecular Neuroscience (766 citations) and Developmental Neuroscience (166 citations). Hongjun Fu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Karen Duff, John Hardy, Qin Ma, Mathieu Herman, Sheina Emrani, S. Abid Hussaini, G Rodriguez, Cankun Wang, Cynthia A. Lemere and Yifan Han. Their work appears in journals such as Nature Neuroscience, International Immunopharmacology, Biochemical and Biophysical Research Communications, Scientific Reports and Neuroscience & Biobehavioral Reviews.

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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