Ying Cha
Impact in
- Immunology top 10%
- interferon and immune responses
- Immune Cell Function and Interaction
- Oncology top 10%
- Cytokine Signaling Pathways and Interactions
- Cancer-related Molecular Pathways
Papers in
-
- Glycosylation and Glycoproteins Research 4
- Ubiquitin and proteasome pathways 2
- Oncology 4
- Cytokine Signaling Pathways and Interactions 3
- Co-authors
- J. Thomas August (4 shared papers)Margaret F. Romine (3 shared papers)Simon H. Sims (3 shared papers)Keith Gottlieb (2 shared papers)Pei-Qing Gao (2 shared papers)Albert Deisseroth (4 shared papers)A. B. Deisseroth (1 shared paper)Craig D. McClain (1 shared paper)
- Journals
- Journal of Biological Chemistry (3 papers)Molecular and Cellular Biology (2 papers)Stem Cells (1 paper)Archives of Biochemistry and Biophysics (1 paper)DNA and Cell Biology (1 paper)
- Partner nations
- United StatesChinaItaly
In The Last Decade
Ying Cha
13 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 85
- Immunology 401
- Oncology 440
- Physiology 68
- Cell Biology 230
- Cancer Research 132
Countries citing papers authored by Ying Cha
This map shows the geographic impact of Ying Cha'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 Cha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Cha more than expected).
Fields of papers citing papers by Ying Cha
This network shows the impact of papers produced by Ying Cha. 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 Cha. The network helps show where Ying Cha may publish in the future.
Co-authors
The 25 scholars most cited alongside Ying Cha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | p53-independent induction of WAF1/CIP1 in human leukemia cells is correlated with growth arrest accompanying monocyte/macrophage differentiation. | 1995 | 244 |
| 2 | 1993 | 241 | |
| 3 | 1993 | 154 | |
| 4 | 1988 | 148 | |
| 5 | 1989 | 147 | |
| 6 | 1993 | 83 | |
| 7 | 1990 | 50 | |
| 8 | Protective effects of berberine on high fat-induced kidney damage by increasing serum adiponectin and promoting insulin sensitivity. | 2015 | 18 |
| 9 | 1992 | 16 | |
| 10 | 2010 | 12 | |
| 11 | 2020 | 11 | |
| 12 | 2016 | 10 | |
| 13 | 1993 | 1 |
About Ying Cha
Ying Cha is a scholar working on Molecular Biology, Oncology, Cell Biology, Immunology and Cancer Research, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (4 papers), Cellular transport and secretion (4 papers), interferon and immune responses (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Lysosomal Storage Disorders Research (2 papers), Berberine and alkaloids research (2 papers), Ubiquitin and proteasome pathways (2 papers) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Immunology (401 citations), Oncology (440 citations), Physiology (68 citations), Cell Biology (230 citations) and Cancer Research (132 citations). Ying Cha has collaborated with scholars based in United States, China and Italy. Frequent co-authors include J. Thomas August, Margaret F. Romine, Simon H. Sims, Keith Gottlieb, Pei-Qing Gao, Albert Deisseroth, A. B. Deisseroth, Craig D. McClain, W E Mercer and Anne M. Gambel. Their work appears in journals such as Journal of Biological Chemistry, Molecular and Cellular Biology, Stem Cells, Archives of Biochemistry and Biophysics and DNA and Cell Biology.
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.