Wei Bai

1.9k citations
37 papers · 1.6k · h-index 20

Impact in

Papers in

    • RNA modifications and cancer 3
    • Peroxisome Proliferator-Activated Receptors 2
    • Muscle Physiology and Disorders 2
    • RNA Interference and Gene Delivery 2
    • Advanced Glycation End Products research 4

Wei Bai

37 papers receiving 1.6k citations

Peers

Wei Bai
Comparison fields: 5 of 107
  • Cancer Research 249
  • Clinical Biochemistry 93
  • Molecular Biology 821
  • Biochemistry 80
  • Immunology 164
Replace Qinglin Yang with:
Qinglin Yang United States
Akira Imaizumi Japan
Ronald J. Holewinski United States
Gary J. Litherland United Kingdom
Kiyomu Fujii Japan
Jeong Han Kang South Korea
Marcelo Lazzaron Lamers Brazil
Caiping Chen China
Anna Shteinfer‐Kuzmine Israel
Wei Bai relative to Qinglin Yang United States Qinglin Yang's profile →
Citations per field
00.5×1.5×
Qinglin Yang · 1×
Citations per year

Countries citing papers authored by Wei Bai

Since Specialization
Citations

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

Fields of papers citing papers by Wei Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000278
2 1997206
3 2005158
4 1997116
5 199989
6 199759
7 199656
8 199756
9 201854
10 202053
11 201844
12 201541
13 201640
14 202139
15 201931
16 202230
17 201624
18 201922
19 201821
20 201921

About Wei Bai

Wei Bai is a scholar working on Molecular Biology, Clinical Biochemistry, Biochemistry, Cancer Research and Physiology, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Eicosanoids and Hypertension Pharmacology (4 papers), Advanced Glycation End Products research (4 papers), Inflammatory mediators and NSAID effects (3 papers), RNA modifications and cancer (3 papers), Peroxisome Proliferator-Activated Receptors (2 papers), Muscle Physiology and Disorders (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Cancer Research (249 citations), Clinical Biochemistry (93 citations), Molecular Biology (821 citations), Biochemistry (80 citations) and Immunology (164 citations). Wei Bai has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Rama D Natarajan, Jerry L. Nadler, Mausumee Guha, Noe Gonzales, Alan E. Tomkinson, Nina Y. Yao, David S. Levin, Jing Zhou, Linda L. Lanting and Jared M. Brown. Their work appears in journals such as Hypertension, Journal of Cachexia Sarcopenia and Muscle, Journal of the American Heart Association, The Journal of Clinical Endocrinology & Metabolism and Journal of Cellular Physiology.

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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