Geok Choo Sim
Impact in
- Immunology top 5%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- T-cell and B-cell Immunology
- Immune cells in cancer
- Oncology top 10%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Immunotherapy and Immune Responses 5
- Immune Cell Function and Interaction 5
- T-cell and B-cell Immunology 3
- Toxin Mechanisms and Immunotoxins 1
- Oncology 4
- Cancer Immunotherapy and Biomarkers 2
- Cytokine Signaling Pathways and Interactions 1
- Co-authors
- Laszlo George Radvanyi (7 shared papers)Patrick Hwu (2 shared papers)Lei Jin (2 shared papers)Sheng Wu (2 shared papers)Luis M. Vence (1 shared paper)Carol L. Lacey (1 shared paper)Yi‐Jun Wang (1 shared paper)Natalia Martín‐Orozco (1 shared paper)
- Journals
- Oncotarget (1 paper)BioResearch open access (1 paper)Cytokine & Growth Factor Reviews (1 paper)Cancer Immunology Research (1 paper)Clinical Cancer Research (1 paper)
- Partner nations
- United StatesGermanyMalaysia
In The Last Decade
Geok Choo Sim
9 papers receiving 727 citations
Peers
Comparison fields: 5 of 73
- Immunology 498
- Oncology 398
- Physiology 20
- Cancer Research 31
- Pulmonary and Respiratory Medicine 60
Countries citing papers authored by Geok Choo Sim
This map shows the geographic impact of Geok Choo Sim'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 Geok Choo Sim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geok Choo Sim more than expected).
Fields of papers citing papers by Geok Choo Sim
This network shows the impact of papers produced by Geok Choo Sim. 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 Geok Choo Sim. The network helps show where Geok Choo Sim may publish in the future.
Co-authors
The 25 scholars most cited alongside Geok Choo Sim, 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 | 2014 | 240 | |
| 2 | 2013 | 202 | |
| 3 | 2009 | 161 | |
| 4 | 2015 | 54 | |
| 5 | 2016 | 38 | |
| 6 | 2014 | 21 | |
| 7 | 2016 | 10 | |
| 8 | 2015 | 9 | |
| 9 | 2012 | 8 |
About Geok Choo Sim
Geok Choo Sim is a scholar working on Immunology, Oncology, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Cardiology and Cardiovascular Medicine, having authored 9 papers that have together received 743 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (5 papers), Immune Cell Function and Interaction (5 papers), T-cell and B-cell Immunology (3 papers), Sarcoma Diagnosis and Treatment (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Toxin Mechanisms and Immunotoxins (1 paper), Cytokine Signaling Pathways and Interactions (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Immunology (498 citations), Oncology (398 citations), Physiology (20 citations), Cancer Research (31 citations) and Pulmonary and Respiratory Medicine (60 citations). Geok Choo Sim has collaborated with scholars based in United States, Germany and Malaysia. Frequent co-authors include Laszlo George Radvanyi, Patrick Hwu, Lei Jin, Sheng Wu, Luis M. Vence, Carol L. Lacey, Yi‐Jun Wang, Natalia Martín‐Orozco, Deborah A. Sanders and Jürgen Christian Becker. Their work appears in journals such as Oncotarget, BioResearch open access, Cytokine & Growth Factor Reviews, Cancer Immunology Research and Clinical Cancer Research.
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.