Kaiting Yang

2.5k citations
29 papers · 1.7k indexed · 3 hit papers · h-index 19

Kaiting Yang

27 papers receiving 1.6k citations

Hit Papers

Zinc cyclic di-AMP nanoparticles target and suppress tumo...154202020262022202450100150200250

Peers

Kaiting Yang
Comparison fields: 5 of 104
  • Immunology 669
  • Oncology 634
  • Biotechnology 155
  • Biological Psychiatry 34
  • Molecular Biology 691
Replace Satoshi Inoue with:
Satoshi Inoue Japan
Pakawat Chongsathidkiet United States
Gabriela B. Ferreira Belgium
Ying Yue China
Irina N. Shalova Singapore
Safa Tahmasebi Iran
Ning Pu China
Nima Hemmat Iran
Rachel H. McMahan United States
Elizabeth F. Redente United States
Kaiting Yang relative to Satoshi Inoue Japan Satoshi Inoue's profile →
Citations per field
00.5×8.5×
Satoshi Inoue · 1×
Citations per year

Countries citing papers authored by Kaiting Yang

Since Specialization
Citations

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

Fields of papers citing papers by Kaiting Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202416
2 202423
3 20243
4 20231
5 20233
6 202318
7 202287
8
Zinc cyclic di-AMP nanoparticles target and suppress tumours via endothelial STING activation and tumour-associated macrophage reinvigorationbreakdown →
2022154
9 20220
10 202138
11 202185
12
Lactobacillus rhamnosus GG induces cGAS/STING- dependent type I interferon and improves response to immune checkpoint blockadebreakdown →
2021220
13 202032
14 20207
15 2019147
16 20185
17 201713
18 20158
19 201318
20 201340

About Kaiting Yang

Kaiting Yang is a scholar working on Immunology, Human Factors and Ergonomics, Oncology, Cancer Research and Occupational Therapy, having authored 29 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (7 papers), Immunotherapy and Immune Responses (7 papers), Immune cells in cancer (7 papers), Immune Cell Function and Interaction (5 papers), interferon and immune responses (4 papers), RNA modifications and cancer (3 papers), Nanoplatforms for cancer theranostics (3 papers) and Respiratory Support and Mechanisms (2 papers). The work is most often cited by research in Immunology (669 citations), Oncology (634 citations), Biotechnology (155 citations), Biological Psychiatry (34 citations) and Molecular Biology (691 citations). Kaiting Yang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Ralph R. Weichselbaum, Yang‐Xin Fu, Martin D. Tobin, Wenbin Lin, Wenxin Zheng, Liangliang Wang, Hua Liang, Kaiyuan Ni, Jason Bugno and Lai Xue. Their work appears in journals such as The Journal of Experimental Medicine, Clinical Cancer Research, Scientific Reports, Blood and Frontiers in Pediatrics.

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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