Ulisses Braga-Neto
- Molecular Biology top 5%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Public Health, Environmental and Occupational Health top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Edward R. DoughertyMahdi ImaniLevi D. McClennyErnesto T. A. MarquesJohn GoutsiasAmin ZollanvariMarli Tenório CordeiroSeyede Fatemeh Ghoreishi
- Topics
- Gene Regulatory Network Analysis (48 papers)Gene expression and cancer classification (39 papers)Statistical Methods and Inference (16 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- United StatesBrazilItaly
In The Last Decade
Ulisses Braga-Neto
134 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Molecular Biology 1.3k
- Artificial Intelligence 636
- Computer Vision and Pattern Recognition 387
- Public Health, Environmental and Occupational Health 340
- Control and Systems Engineering 305
Countries citing papers authored by Ulisses Braga-Neto
This map shows the geographic impact of Ulisses Braga-Neto'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 Ulisses Braga-Neto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulisses Braga-Neto more than expected).
Fields of papers citing papers by Ulisses Braga-Neto
This network shows the impact of papers produced by Ulisses Braga-Neto. 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 Ulisses Braga-Neto. The network helps show where Ulisses Braga-Neto may publish in the future.
Co-authorship network of co-authors of Ulisses Braga-Neto
This figure shows the co-authorship network connecting the top 25 collaborators of Ulisses Braga-Neto. A scholar is included among the top collaborators of Ulisses Braga-Neto 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 Ulisses Braga-Neto. Ulisses Braga-Neto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 21 | |
| 8 | 5 | |
| 9 | 1 | |
| 10 | 51 | |
| 11 | 16 | |
| 12 | 18 | |
| 13 | Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments | 59 |
| 14 | 9 | |
| 15 | 37 | |
| 16 | 10 | |
| 17 | 65 | |
| 18 | 17 | |
| 19 | 12 | |
| 20 | 65 |
About Ulisses Braga-Neto
Ulisses Braga-Neto is a scholar working on Statistics and Probability, Molecular Biology and Artificial Intelligence, having authored 135 papers that have together received 3.4k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (48 papers), Gene expression and cancer classification (39 papers) and Statistical Methods and Inference (16 papers). The work is most often cited by research in Statistics and Probability (197 citations), Artificial Intelligence (636 citations) and Statistics, Probability and Uncertainty (136 citations). Ulisses Braga-Neto has collaborated with scholars based in United States, Brazil and Italy. Frequent co-authors include Edward R. Dougherty, Mahdi Imani, Levi D. McClenny, Ernesto T. A. Marques, John Goutsias, Amin Zollanvari, Marli Tenório Cordeiro, Seyede Fatemeh Ghoreishi, Carlos Alexandre Antunes de Brito and Chenyang Xu. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.