Suxia Bai

1.4k citations
22 papers · 1.0k · h-index 13

Impact in

  • Neurology top 5%
    • Vestibular and auditory disorders
  • Immunology top 10%
    • Immunotherapy and Immune Responses
    • Reproductive System and Pregnancy

Papers in

Suxia Bai

18 papers receiving 1.0k citations

Peers

Suxia Bai
Comparison fields: 5 of 80
  • Neurology 138
  • Immunology 259
  • Sensory Systems 56
  • Obstetrics and Gynecology 75
  • Pulmonary and Respiratory Medicine 299
Replace Melody P. Lun with:
Melody P. Lun United States
Jinsuke Nishino Japan
Süleyman Gülsüner United States
Jo-Anne Herbrick Canada
Marion A. Maw New Zealand
Fabien Guimiot France
Marcelle Jay United Kingdom
Katsumasa Takahashi Japan
Annalena Moliner Sweden
Marie‐Claude Boutterin France
Suxia Bai relative to Melody P. Lun United States Melody P. Lun's profile →
Citations per field
00.5×6.3×
Melody P. Lun · 1×
Citations per year

Countries citing papers authored by Suxia Bai

Since Specialization
Citations

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

Fields of papers citing papers by Suxia Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013182
2 2011126
3 2005119
4 2004113
5 200995
6 200476
7 200169
8 201460
9 200856
10 200947
11 201046
12 200417
13 201616
14 20138
15 20246
16 20244
17
Expression of matrix metalloproteinase--26 in human normal placental cytotrophoblast cells as well as its regulation by activin A
20053
18 20251
19 20250
20 20250

About Suxia Bai

Suxia Bai is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Genetics, Cancer Research and Hematology, having authored 22 papers that have together received 1.0k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (7 papers), Protease and Inhibitor Mechanisms (4 papers), Immunotherapy and Immune Responses (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers), Hormonal and reproductive studies (3 papers), Estrogen and related hormone effects (3 papers), Ubiquitin and proteasome pathways (2 papers) and Heat shock proteins research (2 papers). The work is most often cited by research in Neurology (138 citations), Immunology (259 citations), Sensory Systems (56 citations), Obstetrics and Gynecology (75 citations) and Pulmonary and Respiratory Medicine (299 citations). Suxia Bai has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Elizabeth M. Wilson, Bin He, James L. Mohler, John T. Minges, Caiying Guo, Andrew T. Hnat, Emily B. Askew, Brett D. Mensh, Sacha B. Nelson and Cheng-Chiu Huang. Their work appears in journals such as Journal of Biological Chemistry, Molecular and Cellular Biology, Nature Aging, Molecular and Cellular Endocrinology and Biology of Reproduction.

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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