Xiaobo Shi

28 papers receiving 606 citations

Peers

Xiaobo Shi
Comparison fields: 5 of 79
  • Reproductive Medicine 83
  • Spectroscopy 113
  • Polymers and Plastics 81
  • Bioengineering 27
  • Materials Chemistry 212
Replace Cheng‐Yang Wu with:
Cheng‐Yang Wu United States
Ivan Guryanov Russia
Susan J. Gregory United States
Hanna Nilsson Sweden
Jiehua Ma China
Nozomi Morishita Watanabe Japan
Angelos Thanassoulas Greece
Oriol Penon Spain
Scott Kuzdzal United States
Sureshbabu Nagarajan United States
Xiaobo Shi relative to Cheng‐Yang Wu United States Cheng‐Yang Wu's profile →
Citations per field
00.5×10×16.6×
Cheng‐Yang Wu · 1×
Citations per year

Countries citing papers authored by Xiaobo Shi

Since Specialization
Citations

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

Fields of papers citing papers by Xiaobo Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004194
2 2004124
3 201139
4 201737
5 201131
6 201230
7 200430
8 201628
9 199620
10 202015
11 202314
12 201414
13 202310
14 202010
15
Chronic alcohol administration increases serum prolactin level and pituitary cell proliferation, and alters hypothalamus neurotransmitters in rat.
20117
16 20236
17 20164
18 19954
19
[Study of Chlamydia trachomatis infection on cervical secretion of women with early pregnancy and secondary sterility].
20014
20 20223

About Xiaobo Shi

Xiaobo Shi is a scholar working on Reproductive Medicine, Molecular Biology, Public Health, Environmental and Occupational Health, Cell Biology and Electrical and Electronic Engineering, having authored 28 papers that have together received 634 indexed citations. Recurring topics across this work include Ovarian function and disorders (4 papers), Advanced biosensing and bioanalysis techniques (2 papers), Analytical Chemistry and Sensors (1 paper), Click Chemistry and Applications (1 paper), Organic Electronics and Photovoltaics (1 paper), Gene expression and cancer classification (1 paper), Acupuncture Treatment Research Studies (1 paper) and Polymer Surface Interaction Studies (1 paper). The work is most often cited by research in Reproductive Medicine (83 citations), Spectroscopy (113 citations), Polymers and Plastics (81 citations), Bioengineering (27 citations) and Materials Chemistry (212 citations). Xiaobo Shi has collaborated with scholars based in China, United States and Portugal. Frequent co-authors include Wen‐Sheng Xia, D. McBranch, David G. Whitten, Frauke Rininsland, Komandoor E. Achyuthan, Stuart A. Kushon, Troy S. Bergstedt, Kevin D. Ley, Fufan Zhu and Na Li. Their work appears in journals such as Journal of Assisted Reproduction and Genetics, Proceedings of the National Academy of Sciences, Women s Health, Frontiers in Endocrinology and Biological 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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