D. Vidović
Impact in
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- Computational Drug Discovery Methods
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks
- Peroxisome Proliferator-Activated Receptors
- Metabolism, Diabetes, and Cancer
Papers in
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- SARS-CoV-2 detection and testing 12
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- Bioinformatics and Genomic Networks 8
- Single-cell and spatial transcriptomics 5
- Biomedical Text Mining and Ontologies 5
- Protein Tyrosine Phosphatases 4
- Co-authors
- Stephan C. Schürer (24 shared papers)Patrick R. Griffin (4 shared papers)Theodore M. Kamenecka (3 shared papers)Scott A. Busby (3 shared papers)Gail Wagoner (1 shared paper)Jin Liu (1 shared paper)William R. Roush (1 shared paper)Yongjun Wang (1 shared paper)
- Journals
- The Science of The Total Environment (7 papers)Nucleic Acids Research (6 papers)Bioorganic & Medicinal Chemistry Letters (5 papers)Nature (3 papers)Nature Communications (3 papers)
- Partner nations
- United StatesDenmarkUnited Kingdom
In The Last Decade
D. Vidović
46 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 121
- Computational Theory and Mathematics 488
- Molecular Biology 1.7k
- Immunology 410
- Infectious Diseases 298
- Cancer Research 179
Countries citing papers authored by D. Vidović
This map shows the geographic impact of D. Vidović'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 D. Vidović with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Vidović more than expected).
Fields of papers citing papers by D. Vidović
This network shows the impact of papers produced by D. Vidović. 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 D. Vidović. The network helps show where D. Vidović may publish in the future.
Co-authors
The 25 scholars most cited alongside D. Vidović, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 466 | |
| 2 | 2011 | 458 | |
| 3 | 2017 | 306 | |
| 4 | 2018 | 271 | |
| 5 | 2016 | 210 | |
| 6 | 2017 | 128 | |
| 7 | 2019 | 116 | |
| 8 | 2020 | 110 | |
| 9 | 2022 | 74 | |
| 10 | 2022 | 69 | |
| 11 | 2022 | 65 | |
| 12 | 2014 | 61 | |
| 13 | 2017 | 52 | |
| 14 | 2021 | 43 | |
| 15 | 2010 | 35 | |
| 16 | 2008 | 33 | |
| 17 | 2023 | 32 | |
| 18 | 2022 | 30 | |
| 19 | 2010 | 27 | |
| 20 | 2014 | 26 |
About D. Vidović
D. Vidović is a scholar working on Infectious Diseases, Molecular Biology, Immunology, Biomedical Engineering and Spectroscopy, having authored 48 papers that have together received 2.9k indexed citations. Recurring topics across this work include SARS-CoV-2 detection and testing (12 papers), Biosensors and Analytical Detection (10 papers), Bioinformatics and Genomic Networks (8 papers), Single-cell and spatial transcriptomics (5 papers), Biomedical Text Mining and Ontologies (5 papers), Advanced Proteomics Techniques and Applications (4 papers), Computational Drug Discovery Methods (4 papers) and Protein Tyrosine Phosphatases (4 papers). The work is most often cited by research in Computational Theory and Mathematics (488 citations), Molecular Biology (1.7k citations), Immunology (410 citations), Infectious Diseases (298 citations) and Cancer Research (179 citations). D. Vidović has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include Stephan C. Schürer, Patrick R. Griffin, Theodore M. Kamenecka, Scott A. Busby, Gail Wagoner, Jin Liu, William R. Roush, Yongjun Wang, Jihong Xu and Laura A. Solt. Their work appears in journals such as The Science of The Total Environment, Nucleic Acids Research, Bioorganic & Medicinal Chemistry Letters, Nature and Nature Communications.
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.