Jin Deng

1.1k citations
69 papers · 787 · h-index 18

Impact in

Papers in

Jin Deng

60 papers receiving 782 citations

Peers

Jin Deng
Comparison fields: 5 of 102
  • Endocrinology, Diabetes and Metabolism 163
  • Cancer Research 147
  • Transportation 62
  • Radiology, Nuclear Medicine and Imaging 71
  • Molecular Biology 226
Replace Hayato Ogawa with:
Hayato Ogawa Japan
Fei Teng China
Sharon D. Solomon United States
Matthew Brown United States
Athina Spiliopoulou United Kingdom
José G. Tamez‐Peña Mexico
Heng Shi China
Wei Bian China
Andrea Russo Italy
Jin Deng relative to Hayato Ogawa Japan Hayato Ogawa's profile →
Citations per field
00.5×10.3×
Hayato Ogawa · 1×
Citations per year

Countries citing papers authored by Jin Deng

Since Specialization
Citations

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

Fields of papers citing papers by Jin Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201362
2 202159
3 201458
4 201853
5 201545
6
Prevalence of growth hormone deficiency of children in Beijing.
199234
7 201333
8 202024
9 202223
10 201923
11 201722
12 202121
13 202220
14 202020
15 201818
16 202217
17 202017
18 202017
19 201816
20 202014

About Jin Deng

Jin Deng is a scholar working on Molecular Biology, Cancer Research, Cognitive Neuroscience, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 69 papers that have together received 787 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (12 papers), Functional Brain Connectivity Studies (8 papers), MicroRNA in disease regulation (7 papers), RNA Research and Splicing (5 papers), Sarcoma Diagnosis and Treatment (5 papers), Nerve injury and regeneration (4 papers), EEG and Brain-Computer Interfaces (4 papers) and Transportation Planning and Optimization (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (163 citations), Cancer Research (147 citations), Transportation (62 citations), Radiology, Nuclear Medicine and Imaging (71 citations) and Molecular Biology (226 citations). Jin Deng has collaborated with scholars based in China, United States and Romania. Frequent co-authors include Weiming Zeng, Yuhu Shi, Wei Kong, Xiaoyang Mou, Shuangming Tian, Ying Qian, Yadi Zhu, Zijia Wang, Zexin Chen and Weimin Xu. Their work appears in journals such as PLoS ONE, Scientific Reports, Frontiers in Neuroscience, Combinatorial Chemistry & High Throughput Screening and Molecular Therapy — Nucleic Acids.

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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