Ying Chi

9.5k citations
131 papers · 5.5k indexed · 1 hit paper · h-index 38

Ying Chi

127 papers receiving 5.4k citations

Hit Papers

Human prostate cancer metastases target the hematopoietic...5342011202620162021100200300400500

Peers

Ying Chi
Comparison fields: 5 of 158
  • Genetics 973
  • Immunology 1.5k
  • Oncology 1.8k
  • Cancer Research 782
  • Parasitology 178
Replace Thomas F.E. Barth with:
Thomas F.E. Barth Germany
Atsushi Kawakami Japan
Shigeo Mori Japan
Nathalia A. Giese Germany
Luc J. W. van der Laan Netherlands
Sergij Goerdt Germany
Annette Schmitt‐Graeff Germany
Chul Woo Kim South Korea
Christopher C.W. Hughes United States
Matthew B. Greenblatt United States
Ying Chi relative to Thomas F.E. Barth Germany Thomas F.E. Barth's profile →
Citations per field
00.5×1.7×
Thomas F.E. Barth · 1×
Citations per year

Countries citing papers authored by Ying Chi

Since Specialization
Citations

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

Fields of papers citing papers by Ying Chi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20251
3 20250
4 202326
5 202214
6 202181
7 202018
8 202013
9
Concept Detection based on Multi-label Classification and Image Captioning Approach - DAMO at ImageCLEF 2019.
20194
10 201937
11 201823
12
[Comparison Test Between PM2.5 Continuous Monitoring System and Manual Sampling Analysis for PM2.5 in Ambient Air].
20150
13 2014207
14 2013175
15 201316
16 201327
17 201043
18 2009131
19 200925
20 200843

About Ying Chi

Ying Chi is a scholar working on Genetics, Cancer Research and Immunology, having authored 131 papers that have together received 5.5k indexed citations. Recurring topics across this work include Mesenchymal stem cell research (29 papers), MicroRNA in disease regulation (10 papers), Cancer-related molecular mechanisms research (9 papers), Cancer Cells and Metastasis (7 papers), Parasites and Host Interactions (6 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Immunotherapy and Immune Responses (6 papers) and Extracellular vesicles in disease (6 papers). The work is most often cited by research in Genetics (973 citations), Immunology (1.5k citations) and Oncology (1.8k citations). Ying Chi has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Kenneth J. Pienta, Robert D. Loberg, Zhongchao Han, Zachary S. Varsos, Hernan Roca, Linda A. Snyder, Matthew Craig, Sudha Sud, Yan Li and Chris K. Neeley. Their work appears in journals such as Stem Cell Research & Therapy, Neoplasia, Virology, Cytotherapy and Cellular Physiology and Biochemistry.

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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