Linda Cheung
- Molecular Biology
- Endocrinology, Diabetes and Metabolism top 10%
- Epidemiology
- Artificial Intelligence top 10%
- Genetics
- Co-authors
- Michael KhanStella PelengarisShan E Ahmed RazaD. B. A. EpsteinNasir RajpootMuhammad ShabanSimon GrahamDiana Learoyd
- Topics
- Monoclonal and Polyclonal Antibodies Research (3 papers)HIV Research and Treatment (3 papers)Retinal Development and Disorders (3 papers)
- Journals
- PLoS ONEThe Journal of Clinical Endocrinology & MetabolismJournal of Agricultural and Food Chemistry
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Linda Cheung
26 papers receiving 988 citations
Peers
Comparison fields: 5 of 111
- Molecular Biology 347
- Endocrinology, Diabetes and Metabolism 168
- Epidemiology 152
- Artificial Intelligence 147
- Genetics 141
Countries citing papers authored by Linda Cheung
This map shows the geographic impact of Linda Cheung'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 Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linda Cheung more than expected).
Fields of papers citing papers by Linda Cheung
This network shows the impact of papers produced by Linda Cheung. 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 Cheung. The network helps show where Linda Cheung may publish in the future.
Co-authorship network of co-authors of Linda Cheung
This figure shows the co-authorship network connecting the top 25 collaborators of Linda Cheung. A scholar is included among the top collaborators of Linda Cheung 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 Cheung. Linda Cheung 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 | Understanding Imposter Phenomenon in Graduate Students Using Achievement Goal Theory | 2 |
| 3 | 174 | |
| 4 | 37 | |
| 5 | 44 | |
| 6 | 83 | |
| 7 | 6 | |
| 8 | 18 | |
| 9 | Results of Safety and Tolerability Studies of UshStat®, an EIAV-based Lentiviral-vector Therapy for USH1B and the Elucidation of Retinal Cell Types Responsible for USH1B Pathology | 1 |
| 10 | 40 | |
| 11 | 29 | |
| 12 | Subretinal Delivery Of Eiav-based Lentiviral Vectors In The Shaker1 Mouse Model For Usher Syndrometype 1b : Development Of Ushstat® | 1 |
| 13 | 8 | |
| 14 | 22 | |
| 15 | 51 | |
| 16 | 78 | |
| 17 | 72 | |
| 18 | 152 | |
| 19 | 9 | |
| 20 | 12 |
About Linda Cheung
Linda Cheung is a scholar working on Virology, Nephrology and Biophysics, having authored 26 papers that have together received 1.0k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (3 papers), HIV Research and Treatment (3 papers) and Retinal Development and Disorders (3 papers). The work is most often cited by research in Virology (72 citations), Biophysics (61 citations) and Immunology and Allergy (62 citations). Linda Cheung has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Michael Khan, Stella Pelengaris, Shan E Ahmed Raza, D. B. A. Epstein, Nasir Rajpoot, Muhammad Shaban, Simon Graham, Diana Learoyd, John M. Wentworth and Marinella Messina. Their work appears in journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Journal of Agricultural and Food Chemistry.
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.