Luis Rueda
- Biophysics top 5%
- Artificial Intelligence top 5%
- Algorithms and Data Compression 6
- Signal Processing top 10%
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- Bioinformatics and Genomic Networks 35
- Gene expression and cancer classification 34
- Machine Learning in Bioinformatics 19
- Protein Structure and Dynamics 14
- Single-cell and spatial transcriptomics 6
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- Computational Drug Discovery Methods 15
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- Face and Expression Recognition 10
Luis Rueda
112 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 132
- Biophysics 94
- Computational Mathematics 7
- Artificial Intelligence 289
- Aging 15
- Signal Processing 90
Countries citing papers authored by Luis Rueda
This map shows the geographic impact of Luis Rueda'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 Luis Rueda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luis Rueda more than expected).
Fields of papers citing papers by Luis Rueda
This network shows the impact of papers produced by Luis Rueda. 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 Luis Rueda. The network helps show where Luis Rueda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Luis Rueda, 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 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 23 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 9 | |
| 11 | 2018 | 7 | |
| 12 | 2012 | 1 | |
| 13 | 2011 | 4 | |
| 14 | 2009 | 12 | |
| 15 | Progress in pattern recognition, image analysis and applications : 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 Viña del Mar-Valparaiso, Chile, November 13-16, 2007 : proceedings | 2007 | 6 |
| 16 | 2006 | 33 | |
| 17 | An Unsupervised Learning Scheme for DNA Microarray Image Spot Detection | 2005 | 3 |
| 18 | 2005 | 13 | |
| 19 | 2005 | 27 | |
| 20 | 2003 | 5 |
About Luis Rueda
Luis Rueda is a scholar working on Computational Mathematics, Computational Theory and Mathematics, Molecular Biology, Artificial Intelligence and Biophysics, having authored 122 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (35 papers), Gene expression and cancer classification (34 papers), Machine Learning in Bioinformatics (19 papers), Computational Drug Discovery Methods (15 papers), Protein Structure and Dynamics (14 papers), Face and Expression Recognition (10 papers), Algorithms and Data Compression (6 papers) and Single-cell and spatial transcriptomics (6 papers). The work is most often cited by research in Biophysics (94 citations), Computational Mathematics (7 citations), Artificial Intelligence (289 citations), Aging (15 citations) and Signal Processing (90 citations). Luis Rueda has collaborated with scholars based in Canada, Chile and United States. Frequent co-authors include Abedalrhman Alkhateeb, Alioune Ngom, B. John Oommen, Sherif Saad, Mina Maleki, Waguih ElMaraghy, Dora Cavallo‐Medved, Mehrdad Saif, Lisa A. Porter and Patrick C. K. Hung. Their work appears in journals such as Pattern Recognition, BMC Bioinformatics, Journal of Clinical Oncology, Bioinformatics and Pattern Recognition Letters.
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.