Hui Bai

2.7k citations
112 papers · 2.1k · h-index 27

Impact in

  • Immunology top 5%
    • Immune cells in cancer
    • Atherosclerosis and Cardiovascular Diseases
  • Neurology top 10%
    • Neuroinflammation and Neurodegeneration Mechanisms

Papers in

Hui Bai

103 papers receiving 2.1k citations

Peers

Hui Bai
Comparison fields: 5 of 128
  • Immunology 436
  • Neurology 125
  • Molecular Biology 907
  • Biological Psychiatry 32
  • Cancer Research 184
Replace Ying Nie with:
Ying Nie China
Shaowei Wang China
Mariarosaria Santillo Italy
Wang Jae Lee South Korea
Daniel S. Kikuchi United States
Xiaoyi Hu China
Seung‐Hoon Yang South Korea
Malin Hultqvist Sweden
Eun‐Yi Moon South Korea
Hui Bai relative to Ying Nie China Ying Nie's profile →
Citations per field
00.5×1.5×
Ying Nie · 1×
Citations per year

Countries citing papers authored by Hui Bai

Since Specialization
Citations

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

Fields of papers citing papers by Hui Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011102
2 2019101
3 201185
4 201162
5 202061
6 201259
7 202256
8 201556
9 201352
10 202150
11 201148
12 201047
13 201745
14 201944
15 201238
16 201337
17 201837
18 201933
19 202033
20 201632

About Hui Bai

Hui Bai is a scholar working on Molecular Biology, Immunology, Epidemiology, Plant Science and Surgery, having authored 112 papers that have together received 2.1k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (8 papers), Immune cells in cancer (8 papers), Osteoarthritis Treatment and Mechanisms (8 papers), Anesthesia and Neurotoxicity Research (6 papers), Plant-Microbe Interactions and Immunity (6 papers), Inflammatory mediators and NSAID effects (6 papers), RNA modifications and cancer (5 papers) and NF-κB Signaling Pathways (5 papers). The work is most often cited by research in Immunology (436 citations), Neurology (125 citations), Molecular Biology (907 citations), Biological Psychiatry (32 citations) and Cancer Research (184 citations). Hui Bai has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Jingjing Ben, Xudong Zhu, Hanwen Zhang, Qi Chen, Li Gao, Yong Xu, Zhiheng Zhang, Xiaopeng Song, Tianwen Ma and Qing Yang. Their work appears in journals such as Nature Communications, Biochemical Pharmacology, PLoS ONE, Molecular Neurobiology and Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy.

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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