Dina Khalid
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 detection and testing
- SARS-CoV-2 and COVID-19 Research
- Biomedical Engineering top 10%
- Biosensors and Analytical Detection
Papers in
-
- Advanced biosensing and bioanalysis techniques 1
- Bacillus and Francisella bacterial research 1
- Genetics 2
- Yersinia bacterium, plague, ectoparasites research 1
- Virus-based gene therapy research 1
- Co-authors
- Carla V. Galmozzi (1 shared paper)Daniel Kirrmaier (1 shared paper)Simon Anders (1 shared paper)Lukas P. M. Kremer (1 shared paper)Andrew Freistaedter (1 shared paper)Viet Loan Dao Thi (1 shared paper)Megan L. Stanifer (1 shared paper)Paul Schnitzler (1 shared paper)
- Journals
- Journal of Virology (1 paper)Science Translational Medicine (1 paper)BULGARIAN JOURNAL OF VETERINARY MEDICINE (1 paper)
In The Last Decade
Dina Khalid
3 papers receiving 531 citations
Dina Khalid's Hit Papers
Peers
Comparison fields: 5 of 54
- Infectious Diseases 347
- Biomedical Engineering 355
- Molecular Biology 298
- Modeling and Simulation 8
- Genetics 40
Countries citing papers authored by Dina Khalid
This map shows the geographic impact of Dina Khalid'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 Dina Khalid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dina Khalid more than expected).
Fields of papers citing papers by Dina Khalid
This network shows the impact of papers produced by Dina Khalid. 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 Dina Khalid. The network helps show where Dina Khalid may publish in the future.
Co-authors
The 23 scholars most cited alongside Dina Khalid, 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 | A colorimetric RT-LAMP assay and LAMP-sequencing for detecting SARS-CoV-2 RNA in clinical samples Hit paper breakdown → | 2020 | 499 |
| 2 | 2016 | 41 | |
| 3 | 2021 | 1 |
About Dina Khalid
Dina Khalid is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Cardiology and Cardiovascular Medicine and Epidemiology, having authored 3 papers that have together received 541 indexed citations. Recurring topics across this work include Biosensors and Analytical Detection (1 paper), SARS-CoV-2 detection and testing (1 paper), Yersinia bacterium, plague, ectoparasites research (1 paper), Probiotics and Fermented Foods (1 paper), Advanced biosensing and bioanalysis techniques (1 paper), Herpesvirus Infections and Treatments (1 paper), Bacillus and Francisella bacterial research (1 paper) and Virus-based gene therapy research (1 paper). The work is most often cited by research in Infectious Diseases (347 citations), Biomedical Engineering (355 citations), Molecular Biology (298 citations), Modeling and Simulation (8 citations) and Genetics (40 citations). Dina Khalid has collaborated with scholars based in Germany and Iraq. Frequent co-authors include Carla V. Galmozzi, Daniel Kirrmaier, Simon Anders, Lukas P. M. Kremer, Andrew Freistaedter, Viet Loan Dao Thi, Megan L. Stanifer, Paul Schnitzler, Isabel Barreto Miranda and Kathleen Boerner. Their work appears in journals such as Journal of Virology, Science Translational Medicine and BULGARIAN JOURNAL OF VETERINARY MEDICINE.
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.