Ulisses Braga-Neto
- Statistics and Probability top 2%
- Statistical Methods and Inference 16
- Artificial Intelligence top 2%
- Neural Networks and Applications 10
- Molecular Biology top 5%
- Gene Regulatory Network Analysis 48
- Gene expression and cancer classification 39
- Bioinformatics and Genomic Networks 13
- Single-cell and spatial transcriptomics 9
-
- Control Systems and Identification 12
-
- Smart Agriculture and AI 10
- Co-authors
- Edward R. DoughertyMahdi ImaniLevi D. McClennyErnesto T. A. MarquesJohn GoutsiasAmin ZollanvariMarli Tenório CordeiroSeyede Fatemeh Ghoreishi
- Journals
- SHILAP Revista de lepidopterología (2 papers)Bioinformatics (6 papers)PLoS ONE (4 papers)
- 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
- Statistics and Probability 197
- Artificial Intelligence 636
- Statistics, Probability and Uncertainty 136
- Computer Vision and Pattern Recognition 387
- Molecular Biology 1.3k
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
The 25 scholars most cited alongside Ulisses Braga-Neto, 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 | 2025 | 1 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 4 | |
| 7 | 2022 | 21 | |
| 8 | 2020 | 5 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 51 | |
| 11 | 2019 | 16 | |
| 12 | 2018 | 18 | |
| 13 | Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments | 2018 | 59 |
| 14 | 2018 | 9 | |
| 15 | 2011 | 37 | |
| 16 | 2010 | 10 | |
| 17 | 2009 | 65 | |
| 18 | 2009 | 17 | |
| 19 | 2005 | 12 | |
| 20 | 2004 | 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), Statistical Methods and Inference (16 papers), Bioinformatics and Genomic Networks (13 papers), Control Systems and Identification (12 papers), Smart Agriculture and AI (10 papers), Neural Networks and Applications (10 papers) and Single-cell and spatial transcriptomics (9 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.