Bai‐Xue Han

562 citations
13 papers · 346 · 1 hit paper · h-index 6

Impact in

Papers in

    • Genetic Associations and Epidemiology 7
    • Bioinformatics and Genomic Networks 2
    • Gut microbiota and health 2
    • Metabolism, Diabetes, and Cancer 1

Bai‐Xue Han

12 papers receiving 344 citations

Hit Papers

Causal Relationship Between Gut Microbiota and Autoimmune Diseases: A Two-Sample Mendelian Randomization Study 2022 · 193 citations
1930+1+2Years since publication50100150

Peers

Bai‐Xue Han
Comparison fields: 5 of 72
  • Gastroenterology 38
  • Biological Psychiatry 17
  • Genetics 98
  • Molecular Biology 219
  • Rheumatology 41
Replace Seona Park with:
Seona Park South Korea
Marie Villumsen Denmark
Maya Aharoni Golan Israel
Sylvie Scharl Switzerland
Mario Secondulfo Italy
Aleksandra Sobolewska-Włodarczyk Poland
Katarzyna Sznurkowska Poland
Fotios S. Fousekis Greece
Mikkel Steen Petersen Denmark
Heba Iskandar United States
Bai‐Xue Han relative to Seona Park South Korea Seona Park's profile →
Citations per field
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Seona Park · 1×
Citations per year

Countries citing papers authored by Bai‐Xue Han

Since Specialization
Citations

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

Fields of papers citing papers by Bai‐Xue Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
Causal Relationship Between Gut Microbiota and Autoimmune Diseases: A Two-Sample Mendelian Randomization Study
Hit paper breakdown →
2022193
2 2022107
3 20229
4 20219
5 20228
6 20216
7 20245
8 20233
9 20242
10 20242
11 20231
12 20231
13 20250

About Bai‐Xue Han

Bai‐Xue Han is a scholar working on Genetics, Molecular Biology, Surgery, Cardiology and Cardiovascular Medicine and Epidemiology, having authored 13 papers that have together received 346 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (7 papers), Pancreatic function and diabetes (2 papers), Bioinformatics and Genomic Networks (2 papers), Gut microbiota and health (2 papers), Cardiovascular Function and Risk Factors (1 paper), Bone health and treatments (1 paper), Metabolism, Diabetes, and Cancer (1 paper) and Celiac Disease Research and Management (1 paper). The work is most often cited by research in Gastroenterology (38 citations), Biological Psychiatry (17 citations), Genetics (98 citations), Molecular Biology (219 citations) and Rheumatology (41 citations). Bai‐Xue Han has collaborated with scholars based in China. Frequent co-authors include Qian Xu, Yu‐Fang Pei, Shanshan Yan, Jing‐Jing Ni, Xin‐Tong Wei, Guijuan Feng, Hong Zhang, Lei Zhang, Bin Li and Min Zhao. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Frontiers in Microbiology, BMJ Open Diabetes Research & Care, Frontiers in Endocrinology and Cellular and Molecular Neurobiology.

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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