Xin Jin

99 papers receiving 1.7k citations

Peers

Xin Jin
Comparison fields: 5 of 102
  • Endocrine and Autonomic Systems 193
  • Aging 32
  • Cellular and Molecular Neuroscience 319
  • Hematology 150
  • Oncology 336
Replace Michael D. Conkright with:
Michael D. Conkright United States
Sylvane Desrivières United Kingdom
Kevin A. Kelley United States
Niamh X. Cawley United States
Alexander C. Zambon United States
Erich F. Greiner Germany
Young Ho Suh South Korea
Pieter J. Peeters Belgium
Hideo Taniura Japan
Mieczysław Marcinkiewicz Canada
Xin Jin relative to Michael D. Conkright United States Michael D. Conkright's profile →
Citations per field
00.5×6.2×
Michael D. Conkright · 1×
Citations per year

Countries citing papers authored by Xin Jin

Since Specialization
Citations

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

Fields of papers citing papers by Xin Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 107 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019116
2 2015106
3 201779
4 200874
5 202164
6 202050
7 202150
8 201850
9 201641
10 201340
11 202340
12 201038
13 201737
14 201135
15 201732
16 202032
17 201329
18 200928
19 201026
20 201125

About Xin Jin

Xin Jin is a scholar working on Molecular Biology, Oncology, Cellular and Molecular Neuroscience, Genetics and Immunology, having authored 107 papers that have together received 1.7k indexed citations. Recurring topics across this work include CAR-T cell therapy research (15 papers), Circular RNAs in diseases (9 papers), Virus-based gene therapy research (8 papers), Neuropeptides and Animal Physiology (8 papers), Nitric Oxide and Endothelin Effects (8 papers), MicroRNA in disease regulation (7 papers), Cancer-related molecular mechanisms research (6 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (193 citations), Aging (32 citations), Cellular and Molecular Neuroscience (319 citations), Hematology (150 citations) and Oncology (336 citations). Xin Jin has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Mingfeng Zhao, Chun Jiang, Wenyi Lu, Hiromu Kawasaki, Yoshito Zamami, Ningren Cui, Xiaoyuan He, Michael N. Nitabach, Shingo Takatori and Yoshihisa Kitamura. Their work appears in journals such as Journal of Pharmacological Sciences, American Journal of Physiology-Cell Physiology, Environmental Progress & Sustainable Energy, British Journal of Pharmacology and Blood.

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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