Gek Kee Sim
Impact in
- Molecular Biology top 2%
- RNA and protein synthesis mechanisms
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- RNA Interference and Gene Delivery
- Genetics top 2%
- Virus-based gene therapy research
- Animal Genetics and Reproduction
Papers in
-
- CRISPR and Genetic Engineering 3
- DNA Repair Mechanisms 1
- Glycosylation and Glycoproteins Research 1
-
- T-cell and B-cell Immunology 4
- Immunotherapy and Immune Responses 2
- Co-authors
- Tom Maniatis (2 shared papers)Elizabeth Lacy (2 shared papers)Argiris Efstratiadis (1 shared paper)Ross C. Hardison (1 shared paper)Diana Quon (1 shared paper)Catherine M. O’Connell (1 shared paper)Àngel Pellicer (2 shared papers)Saul J. Silverstein (2 shared papers)
- Journals
- Cell (3 papers)Veterinary Immunology and Immunopathology (2 papers)Annals of the New York Academy of Sciences (1 paper)Science (1 paper)Nature (1 paper)
- Partner nations
- United States
In The Last Decade
Gek Kee Sim
8 papers receiving 3.1k citations
Gek Kee Sim's Hit Papers
Peers
Comparison fields: 5 of 107
- Molecular Biology 2.5k
- Genetics 928
- Immunology 657
- Virology 86
- Radiology, Nuclear Medicine and Imaging 379
Countries citing papers authored by Gek Kee Sim
This map shows the geographic impact of Gek Kee 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 Gek Kee Sim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gek Kee Sim more than expected).
Fields of papers citing papers by Gek Kee Sim
This network shows the impact of papers produced by Gek Kee 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 Gek Kee Sim. The network helps show where Gek Kee Sim may publish in the future.
Co-authors
The 25 scholars most cited alongside Gek Kee 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 | The isolation of structural genes from libraries of eucaryotic DNA Hit paper breakdown → | 1978 | 1703 |
| 2 | Transformation of mammalian cells with genes from procaryotes and eucaryotes Hit paper breakdown → | 1979 | 1339 |
| 3 | 1984 | 208 | |
| 4 | 1980 | 190 | |
| 5 | 1984 | 51 | |
| 6 | 1999 | 17 | |
| 7 | 1983 | 10 | |
| 8 | 2001 | 10 |
About Gek Kee Sim
Gek Kee Sim is a scholar working on Molecular Biology, Immunology, Oncology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 8 papers that have together received 3.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (4 papers), CRISPR and Genetic Engineering (3 papers), Immunotherapy and Immune Responses (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Virus-based gene therapy research (2 papers), DNA Repair Mechanisms (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Peptidase Inhibition and Analysis (1 paper). The work is most often cited by research in Molecular Biology (2.5k citations), Genetics (928 citations), Immunology (657 citations), Virology (86 citations) and Radiology, Nuclear Medicine and Imaging (379 citations). Gek Kee Sim has collaborated with scholars based in United States. Frequent co-authors include Tom Maniatis, Elizabeth Lacy, Argiris Efstratiadis, Ross C. Hardison, Diana Quon, Catherine M. O’Connell, Àngel Pellicer, Saul J. Silverstein, B Wold and Richard Axel. Their work appears in journals such as Cell, Veterinary Immunology and Immunopathology, Annals of the New York Academy of Sciences, Science and Nature.
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.