Linda Wong
- Molecular Biology top 5%
- Cancer Research top 1%
- Political Science and International Relations top 5%
- Sociology and Political Science top 10%
- Immunology
- Co-authors
- Caifu ChenDana RidzonYu LiangChris HaqqDavid G. GinzingerJessica BowersVita FedeleMichael Mattie
- Topics
- MicroRNA in disease regulation (8 papers)Cancer-related molecular mechanisms research (5 papers)Economic and Environmental Valuation (2 papers)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Linda Wong
30 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Molecular Biology 1.7k
- Cancer Research 1.5k
- Political Science and International Relations 161
- Sociology and Political Science 135
- Immunology 122
Countries citing papers authored by Linda Wong
This map shows the geographic impact of Linda Wong'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 Linda Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linda Wong more than expected).
Fields of papers citing papers by Linda Wong
This network shows the impact of papers produced by Linda Wong. 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 Linda Wong. The network helps show where Linda Wong may publish in the future.
Co-authorship network of co-authors of Linda Wong
This figure shows the co-authorship network connecting the top 25 collaborators of Linda Wong. A scholar is included among the top collaborators of Linda Wong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Linda Wong. Linda Wong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 12 | |
| 6 | 74 | |
| 7 | 139 | |
| 8 | 126 | |
| 9 | 4 | |
| 10 | 38 | |
| 11 | 10 | |
| 12 | Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies.breakdown → | 589 |
| 13 | 54 | |
| 14 | 22 | |
| 15 | 51 | |
| 16 | 2 | |
| 17 | Multiplex gene expression analysis for high-throughput drug discovery: screening and analysis of compounds affecting genes overexpressed in cancer cells. | 53 |
| 18 | 154 | |
| 19 | "Dios" y "Dioses" en el "Libro de Alexandre" | 4 |
| 20 | 25 |
About Linda Wong
Linda Wong is a scholar working on Cancer Research, Aquatic Science and Hematology, having authored 30 papers that have together received 2.4k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (8 papers), Cancer-related molecular mechanisms research (5 papers) and Economic and Environmental Valuation (2 papers). The work is most often cited by research in Cancer Research (1.5k citations), Molecular Biology (1.7k citations) and Obstetrics and Gynecology (96 citations). Linda Wong has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Caifu Chen, Dana Ridzon, Yu Liang, Chris Haqq, David G. Ginzinger, Jessica Bowers, Vita Fedele, Michael Mattie, Christopher C. Benz and Gary K. Scott. Their work appears in journals such as Nucleic Acids Research, Cancer Research and Scientific Reports.
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.