Dinler A. Antunes
- Molecular Biology
- Immunology top 10%
- Computational Theory and Mathematics top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Co-authors
- Lydia E. KavrakiDidier DevaursMaurício RigoGregory LizéeMark MollGustavo Fioravanti VieiraMarialva SinigagliaCecilia Clementi
- Topics
- vaccines and immunoinformatics approaches (20 papers)Immunotherapy and Immune Responses (12 papers)Monoclonal and Polyclonal Antibodies Research (10 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- United StatesBrazilGermany
In The Last Decade
Dinler A. Antunes
43 papers receiving 936 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Molecular Biology 644
- Immunology 319
- Computational Theory and Mathematics 164
- Radiology, Nuclear Medicine and Imaging 158
- Oncology 116
Countries citing papers authored by Dinler A. Antunes
This map shows the geographic impact of Dinler A. Antunes'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 Dinler A. Antunes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dinler A. Antunes more than expected).
Fields of papers citing papers by Dinler A. Antunes
This network shows the impact of papers produced by Dinler A. Antunes. 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 Dinler A. Antunes. The network helps show where Dinler A. Antunes may publish in the future.
Co-authorship network of co-authors of Dinler A. Antunes
This figure shows the co-authorship network connecting the top 25 collaborators of Dinler A. Antunes. A scholar is included among the top collaborators of Dinler A. Antunes 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 Dinler A. Antunes. Dinler A. Antunes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 0 | |
| 10 | Current progress and open challenges for applying deep learning across the biosciencesbreakdown → | 171 |
| 11 | 7 | |
| 12 | 6 | |
| 13 | 7 | |
| 14 | 34 | |
| 15 | 93 | |
| 16 | 19 | |
| 17 | 91 | |
| 18 | 3 | |
| 19 | Reconstruction of MHC Alleles by Cross Modeling and Structural Assessment. | 1 |
| 20 | 11 |
About Dinler A. Antunes
Dinler A. Antunes is a scholar working on Immunology, Hepatology and Molecular Biology, having authored 48 papers that have together received 945 indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (20 papers), Immunotherapy and Immune Responses (12 papers) and Monoclonal and Polyclonal Antibodies Research (10 papers). The work is most often cited by research in Immunology (319 citations), Computational Theory and Mathematics (164 citations) and Molecular Biology (644 citations). Dinler A. Antunes has collaborated with scholars based in United States, Brazil and Germany. Frequent co-authors include Lydia E. Kavraki, Didier Devaurs, Maurício Rigo, Gregory Lizée, Mark Moll, Gustavo Fioravanti Vieira, Marialva Sinigaglia, Cecilia Clementi, R. A. Leo Elworth and Advait Balaji. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.
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.