Ren Yi

874 citations
15 papers · 538 · h-index 7

Impact in

  • Immunology top 10%
    • Immune Cell Function and Interaction
    • IL-33, ST2, and ILC Pathways
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses

Papers in

    • Single-cell and spatial transcriptomics 1
    • Machine Learning in Bioinformatics 1
    • Immune Cell Function and Interaction 3
    • IL-33, ST2, and ILC Pathways 2

Ren Yi

13 papers receiving 531 citations

Peers

Ren Yi
Comparison fields: 5 of 71
  • Immunology 285
  • Biological Psychiatry 14
  • Gastroenterology 29
  • Infectious Diseases 68
  • Molecular Biology 251
Replace Sophie Van Welden with:
Sophie Van Welden Belgium
Heather Evans‐Marin United States
Martina Lubrano di Ricco France
Justin B. Moroney United States
Iulia Oancea Australia
Meifang Huang China
Daniel Peltier United States
Alban Giese France
Ritian Lin China
Helia N. Sanchez United States
Ren Yi relative to Sophie Van Welden Belgium Sophie Van Welden's profile →
Citations per field
00.5×2.5×
Sophie Van Welden · 1×
Citations per year

Countries citing papers authored by Ren Yi

Since Specialization
Citations

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

Fields of papers citing papers by Ren Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2018354
2 201961
3 202237
4 202037
5 202221
6 202212
7 20227
8 20252
9
[Butyrate increases the monocytic myeloid-derived suppressor cells and promotes the secretion of anti-inflammatory cytokines in mice with alcoholic liver disease].
20222
10 20242
11 20221
12 20251
13 20251
14 20250
15 20250

About Ren Yi

Ren Yi is a scholar working on Molecular Biology, Immunology, Surgery, Epidemiology and Nutrition and Dietetics, having authored 15 papers that have together received 538 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (3 papers), Fatty Acid Research and Health (2 papers), IL-33, ST2, and ILC Pathways (2 papers), Single-cell and spatial transcriptomics (1 paper), Machine Learning in Bioinformatics (1 paper), Cell Image Analysis Techniques (1 paper), Quinazolinone synthesis and applications (1 paper) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Immunology (285 citations), Biological Psychiatry (14 citations), Gastroenterology (29 citations), Infectious Diseases (68 citations) and Molecular Biology (251 citations). Ren Yi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Richard Bonneau, Dan R. Littman, Maria Pokrovskii, Christy Au, Carolina Galan, Yasmine Belkaid, Yi Ding, Oliver J. Harrison, Mo Xu and Nicholas Carriero. Their work appears in journals such as Bioinformatics, European Journal of Medicinal Chemistry, Journal of Functional Foods, Nature Communications and Immunity.

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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