Axel J. Soto
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- Computational Drug Discovery Methods 9
- Artificial Intelligence top 10%
- Topic Modeling 8
- Natural Language Processing Techniques 4
- Advanced Text Analysis Techniques 4
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- Biomedical Text Mining and Ontologies 7
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- Data Visualization and Analytics 4
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- Expert finding and Q&A systems 3
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- Species Distribution and Climate Change 3
- Co-authors
- Ignacio PonzoniPiotr PrzybyłaGustavo E. VázquezSophia AnaniadouEvangelos MiliosMaría Jimena MartínezStephen BrooksMarc Strickert
- Partner nations
- CanadaArgentinaUnited Kingdom
In The Last Decade
Axel J. Soto
32 papers receiving 285 citations
Peers
Comparison fields: 5 of 89
- Computational Theory and Mathematics 93
- Artificial Intelligence 107
- Health Informatics 3
- Signal Processing 23
- Statistical and Nonlinear Physics 26
Countries citing papers authored by Axel J. Soto
This map shows the geographic impact of Axel J. Soto'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 Axel J. Soto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Axel J. Soto more than expected).
Fields of papers citing papers by Axel J. Soto
This network shows the impact of papers produced by Axel J. Soto. 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 Axel J. Soto. The network helps show where Axel J. Soto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Axel J. Soto, 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 | 2024 | 0 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 11 | |
| 5 | 2021 | 2 | |
| 6 | 2019 | 0 | |
| 7 | 2018 | 7 | |
| 8 | 2018 | 12 | |
| 9 | 2017 | 15 | |
| 10 | Identifying Personalised Treatments and Clinical Trials for Precision Medicine using Semantic Search with Thalia | 2017 | 1 |
| 11 | 2016 | 11 | |
| 12 | 2016 | 1 | |
| 13 | 2015 | 23 | |
| 14 | 2015 | 7 | |
| 15 | 2015 | 4 | |
| 16 | 2013 | 9 | |
| 17 | 2013 | 2 | |
| 18 | 2012 | 10 | |
| 19 | Adaptive matrix distances aiming at optimum regression subspaces. | 2010 | 4 |
| 20 | 2009 | 39 |
About Axel J. Soto
Axel J. Soto is a scholar working on Ecological Modeling, Artificial Intelligence and Computational Theory and Mathematics, having authored 37 papers that have together received 298 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Topic Modeling (8 papers), Biomedical Text Mining and Ontologies (7 papers), Data Visualization and Analytics (4 papers), Natural Language Processing Techniques (4 papers), Advanced Text Analysis Techniques (4 papers), Expert finding and Q&A systems (3 papers) and Species Distribution and Climate Change (3 papers). The work is most often cited by research in Computational Theory and Mathematics (93 citations), Artificial Intelligence (107 citations) and Health Informatics (3 citations). Axel J. Soto has collaborated with scholars based in Canada, Argentina and United Kingdom. Frequent co-authors include Ignacio Ponzoni, Piotr Przybyła, Gustavo E. Vázquez, Sophia Ananiadou, Evangelos Milios, María Jimena Martínez, Stephen Brooks, Marc Strickert, Mónica F. Díaz and Nhung T. H. Nguyen. Their work appears in journals such as Bioinformatics, PLoS ONE and Analytical Chemistry.
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.