Dexi Bi

3.6k citations
48 papers · 2.6k indexed · 4 hit papers · h-index 24

Dexi Bi

46 papers receiving 2.5k citations

Hit Papers

Fusobacterium nuclea...492018202620202023100200300

Peers

Dexi Bi
Comparison fields: 5 of 130
  • Molecular Medicine 551
  • Endocrinology 374
  • Microbiology 104
  • Molecular Biology 1.1k
  • Infectious Diseases 293
Replace Igor Tolstoy with:
Igor Tolstoy United States
María López Spain
Annemieke Smet Belgium
Hee Young Kang South Korea
Jiahui Li China
Silke Peter Germany
Lihua Guo China
Masato Suzuki Japan
Yan Chen China
Chih‐Yu Chen Taiwan
Dexi Bi relative to Igor Tolstoy United States Igor Tolstoy's profile →
Citations per field
00.5×1.5×2.1×
Igor Tolstoy · 1×
Citations per year

Countries citing papers authored by Dexi Bi

Since Specialization
Citations

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

Fields of papers citing papers by Dexi Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20257
2 20250
3 202317
4 20235
5 20229
6
Ketogenic diet for human diseases: the underlying mechanisms and potential for clinical implementationsbreakdown →
2022237
7 202222
8 202211
9 202023
10 201958
11 201938
12 20164
13 201520
14 201549
15 201248
16 201291
17 20113
18 2011170
19 201011
20 200714

About Dexi Bi

Dexi Bi is a scholar working on Molecular Medicine, Endocrinology, Gastroenterology, Infectious Diseases and Biotechnology, having authored 48 papers that have together received 2.6k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (9 papers), Gut microbiota and health (8 papers), Bacteriophages and microbial interactions (7 papers), Bacterial Genetics and Biotechnology (7 papers), Genomics and Phylogenetic Studies (6 papers), Vibrio bacteria research studies (5 papers), Mycobacterium research and diagnosis (5 papers) and Clostridium difficile and Clostridium perfringens research (4 papers). The work is most often cited by research in Molecular Medicine (551 citations), Endocrinology (374 citations), Microbiology (104 citations), Molecular Biology (1.1k citations) and Infectious Diseases (293 citations). Dexi Bi has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Hong‐Yu Ou, Cui Tai, Zixin Deng, Kumar Rajakumar, Yingzhou Xie, Xinyi He, Huiyuan Zhu, Ewan M. Harrison, Huanlong Qin and Xiaobin Li. Their work appears in journals such as Nucleic Acids Research, Antimicrobial Agents and Chemotherapy, Nature Communications, IEEE/ASME Transactions on Mechatronics and Journal of Bacteriology.

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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