Ning Go
Impact in
- Immunology top 5%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Immune Response and Inflammation
- Immunodeficiency and Autoimmune Disorders
- Oncology top 10%
Papers in
- Oncology 6
- Cancer Cells and Metastasis 2
-
- Telomeres, Telomerase, and Senescence 6
- Co-authors
- Anne O’Garra (1 shared paper)Maureen Howard (1 shared paper)Geoffrey Haughton (1 shared paper)M Howard (2 shared papers)Rob Kastelein (1 shared paper)Kevin W. Moore (1 shared paper)Rachel Barrett (1 shared paper)Tim R. Mosmann (1 shared paper)
- Journals
- Blood (2 papers)Annals of Translational Medicine (2 papers)Cancer Research (2 papers)Clinical Cancer Research (1 paper)The Journal of Immunology (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Ning Go
20 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 93
- Immunology 726
- Oncology 288
- Genetics 100
- Physiology 210
- Biotechnology 70
Countries citing papers authored by Ning Go
This map shows the geographic impact of Ning Go'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 Ning Go with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Go more than expected).
Fields of papers citing papers by Ning Go
This network shows the impact of papers produced by Ning Go. 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 Ning Go. The network helps show where Ning Go may publish in the future.
Co-authors
The 25 scholars most cited alongside Ning Go, 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 | 1992 | 461 | |
| 2 | 1990 | 447 | |
| 3 | 2002 | 145 | |
| 4 | 2005 | 121 | |
| 5 | 2010 | 116 | |
| 6 | 2010 | 70 | |
| 7 | 2018 | 59 | |
| 8 | 1989 | 56 | |
| 9 | 2000 | 45 | |
| 10 | 2019 | 9 | |
| 11 | 1998 | 8 | |
| 12 | 2011 | 5 | |
| 13 | 2017 | 5 | |
| 14 | 2017 | 5 | |
| 15 | 2020 | 4 | |
| 16 | 2010 | 4 | |
| 17 | 2021 | 2 | |
| 18 | 2010 | 1 | |
| 19 | 2012 | 1 | |
| 20 | 2019 | 1 |
About Ning Go
Ning Go is a scholar working on Oncology, Physiology, Molecular Biology, Biotechnology and Computational Theory and Mathematics, having authored 20 papers that have together received 1.6k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (6 papers), Cancer Research and Treatments (4 papers), Liver physiology and pathology (3 papers), Computational Drug Discovery Methods (3 papers), Estrogen and related hormone effects (3 papers), T-cell and B-cell Immunology (2 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Immunology (726 citations), Oncology (288 citations), Genetics (100 citations), Physiology (210 citations) and Biotechnology (70 citations). Ning Go has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Anne O’Garra, Maureen Howard, Geoffrey Haughton, M Howard, Rob Kastelein, Kevin W. Moore, Rachel Barrett, Tim R. Mosmann, Brian E. Castle and Calvin B. Harley. Their work appears in journals such as Blood, Annals of Translational Medicine, Cancer Research, Clinical Cancer Research and The Journal of Immunology.
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.