Gen Yan

844 citations
49 papers · 639 indexed · h-index 17

Impact in

Papers in

Gen Yan

44 papers receiving 633 citations

Peers

Gen Yan
Comparison fields: 5 of 89
  • Biological Psychiatry 84
  • Behavioral Neuroscience 77
  • Developmental Neuroscience 47
  • Neurology 76
  • Radiology, Nuclear Medicine and Imaging 174
Replace Manfred Bauer with:
Manfred Bauer Germany
Lisa Wells United Kingdom
Yi Liao China
Ailsa L. McGregor New Zealand
А. Е. Акулов Russia
Douglass Vines Canada
Kenneth A. Jenrow United States
Jouni Tuisku Finland
Bang‐Hung Yang Taiwan
Yutian Zhan United States
Gen Yan relative to Manfred Bauer Germany Manfred Bauer's profile →
Citations per field
00.5×3.3×
Manfred Bauer · 1×
Citations per year

Countries citing papers authored by Gen Yan

Since Specialization
Citations

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

Fields of papers citing papers by Gen Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201569
2 202259
3 201542
4 201628
5 201227
6 201627
7 201525
8 201423
9 201422
10 201622
11 201420
12 201620
13 202020
14 201919
15 201718
16 202317
17 201416
18 201416
19 202216
20 201913

About Gen Yan

Gen Yan is a scholar working on Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience, Pulmonary and Respiratory Medicine, Materials Chemistry and Molecular Biology, having authored 49 papers that have together received 639 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (15 papers), MRI in cancer diagnosis (12 papers), Neuroscience and Neuropharmacology Research (9 papers), Advanced Neuroimaging Techniques and Applications (9 papers), Lanthanide and Transition Metal Complexes (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Tryptophan and brain disorders (5 papers) and Neurogenesis and neuroplasticity mechanisms (4 papers). The work is most often cited by research in Biological Psychiatry (84 citations), Behavioral Neuroscience (77 citations), Developmental Neuroscience (47 citations), Neurology (76 citations) and Radiology, Nuclear Medicine and Imaging (174 citations). Gen Yan has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Renhua Wu, Haiyun Xu, Zhuozhi Dai, Qingjun Huang, Zhiwei Shen, Yunjuan Nie, Hui Peng, Yuan Shao, Guishan Zhang and Gang Xiao. Their work appears in journals such as Scientific Reports, Journal of X-Ray Science and Technology, ACS Chemical Neuroscience, PLoS ONE and Neurochemical Research.

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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