Jin Han

128 papers receiving 5.3k citations

Jin Han's Hit Papers

The senescence-associated secretory phenotype and its physiological and pathological implications 2024 · 282 citations
2820+2+5Years since publication100200300

Peers

Jin Han
Comparison fields: 5 of 175
  • Developmental Neuroscience 297
  • Biomaterials 771
  • Genetics 412
  • Biomedical Engineering 1.5k
  • Marketing 302
Replace Chien‐Wen Chen with:
Chien‐Wen Chen Taiwan
Yang Xu China
Ying Qu China
Suping Chen China
Yong Xu China
Erik Sundström Sweden
So Ra Park South Korea
Richard B. Robinson United States
Stefan Karlsson Sweden
Michael M. Shen United States
Jin Han relative to Chien‐Wen Chen Taiwan Chien‐Wen Chen's profile →
Citations per field
00.5×4.3×
Chien‐Wen Chen · 1×
Citations per year

Countries citing papers authored by Jin Han

Since Specialization
Citations

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

Fields of papers citing papers by Jin Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 132 papers — load more, or switch the sort, to bring in the rest.

#Work
1
M1 Macrophage-Derived Nanovesicles Potentiate the Anticancer Efficacy of Immune Checkpoint Inhibitors
Hit paper breakdown →
2018381
2
The senescence-associated secretory phenotype and its physiological and pathological implications
Hit paper breakdown →
2024282
3 2011236
4 2001226
5 2018217
6 2015201
7 2020186
8 2016174
9 2005154
10 2013154
11 2006140
12 2015119
13 2015114
14 2020103
15 2013101
16 2006101
17 200999
18 200891
19 200891
20 201579

About Jin Han

Jin Han is a scholar working on Molecular Biology, Surgery, Biomedical Engineering, Genetics and Cellular and Molecular Neuroscience, having authored 132 papers that have together received 5.4k indexed citations. Recurring topics across this work include Tissue Engineering and Regenerative Medicine (18 papers), Mesenchymal stem cell research (15 papers), Pluripotent Stem Cells Research (14 papers), Nerve injury and regeneration (11 papers), 3D Printing in Biomedical Research (10 papers), Neurogenesis and neuroplasticity mechanisms (9 papers), Electrospun Nanofibers in Biomedical Applications (7 papers) and Optical Network Technologies (7 papers). The work is most often cited by research in Developmental Neuroscience (297 citations), Biomaterials (771 citations), Genetics (412 citations), Biomedical Engineering (1.5k citations) and Marketing (302 citations). Jin Han has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Jianwu Dai, Byung‐Soo Kim, Zhifeng Xiao, Woo Gon Kim, Bing Chen, Jennifer H. Elisseeff, Yannan Zhao, Euehun Lee, Boshi Wang and Marco Demaria. Their work appears in journals such as Biomaterials, ACS Nano, Stem Cells, Biochemical and Biophysical Research Communications and Advanced Materials.

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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