Li-Xin Shan

1.3k citations
17 papers · 1.1k indexed · h-index 11
Topics
Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers)Receptor Mechanisms and Signaling (4 papers)Neuropeptides and Animal Physiology (4 papers)

In The Last Decade

Li-Xin Shan

17 papers receiving 1.0k citations

Peers

Li-Xin Shan
Comparison fields: 5 of 95
  • Molecular Biology 386
  • Surgery 262
  • Cellular and Molecular Neuroscience 206
  • Reproductive Medicine 184
  • Immunology 169
Replace Olivier Lahuna with:
Olivier Lahuna France
Jin K. Kim United States
Ingrid C. Gaemers Netherlands
Sandra L. Grimm United States
Hajime Ishida Japan
Juanita A. Archer United States
Emma Hudson United Kingdom
S ALI United States
P. G. H. Byfield United Kingdom
Chihiro Yamazaki Japan
Li-Xin Shan relative to Olivier Lahuna France Olivier Lahuna's profile →
Citations per field
00.5×6.3×
Olivier Lahuna · 1×
Citations per year

Countries citing papers authored by Li-Xin Shan

Since Specialization
Citations

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

Fields of papers citing papers by Li-Xin Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li-Xin Shan

This figure shows the co-authorship network connecting the top 25 collaborators of Li-Xin Shan. A scholar is included among the top collaborators of Li-Xin Shan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Li-Xin Shan. Li-Xin Shan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 3
2 3
3 8
4 6
5 72
6 67
7 2
8 146
9 40
10 94
11 28
12 92
13 3
14 117
15 82
16 169
17 120

About Li-Xin Shan

Li-Xin Shan is a scholar working on Reproductive Medicine, Cellular and Molecular Neuroscience and Spectroscopy, having authored 17 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers), Receptor Mechanisms and Signaling (4 papers) and Neuropeptides and Animal Physiology (4 papers). The work is most often cited by research in Reproductive Medicine (184 citations), Endocrine and Autonomic Systems (82 citations) and Cellular and Molecular Neuroscience (206 citations). Li-Xin Shan has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Joseph A. Hedrick, Matthew P. Hardy, Lauri Benton, Ling Pang, Olli A. Jänne, Marina Rodríguez, Lan Hong, Eric L. Gustafson, Marvin Bayne and Nicholas Murgolo. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and Analytical Chemistry.

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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