José Ignacio Abreu

508 total citations
35 papers, 391 citations indexed

About

José Ignacio Abreu is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, José Ignacio Abreu has authored 35 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 14 papers in Molecular Biology and 7 papers in Computational Theory and Mathematics. Recurrent topics in José Ignacio Abreu's work include Protein Structure and Dynamics (8 papers), Machine Learning in Bioinformatics (7 papers) and Computational Drug Discovery Methods (7 papers). José Ignacio Abreu is often cited by papers focused on Protein Structure and Dynamics (8 papers), Machine Learning in Bioinformatics (7 papers) and Computational Drug Discovery Methods (7 papers). José Ignacio Abreu collaborates with scholars based in Cuba, Spain and Chile. José Ignacio Abreu's co-authors include Michael Fernández, Julio Caballero, Leyden Fernández, A.G. López‐Herrera, Miguel Garriga, Simona Collina, Juan Ramón Rico-Juan, Amanda S. Barnard, Hongqing Shi and Yoan Gutiérrez and has published in prestigious journals such as IEEE Access, Proteins Structure Function and Bioinformatics and Applied Soft Computing.

In The Last Decade

José Ignacio Abreu

30 papers receiving 383 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
José Ignacio Abreu Cuba 9 161 129 108 59 27 35 391
Chris Williams United States 6 199 1.2× 152 1.2× 203 1.9× 35 0.6× 76 2.8× 12 529
Alex G. C. de Sá Australia 9 121 0.8× 91 0.7× 92 0.9× 28 0.5× 24 0.9× 23 349
Ying Yin China 10 131 0.8× 51 0.4× 37 0.3× 30 0.5× 10 0.4× 33 357
Huijun Wang United States 8 237 1.5× 105 0.8× 193 1.8× 60 1.0× 11 0.4× 22 400
Haidong Lan China 11 179 1.1× 76 0.6× 58 0.5× 24 0.4× 17 0.6× 19 306
Dmitrii N. Rassokhin United States 13 182 1.1× 40 0.3× 199 1.8× 93 1.6× 21 0.8× 20 398
Stefan M. Kohlbacher Austria 6 162 1.0× 67 0.5× 250 2.3× 203 3.4× 34 1.3× 8 391
Nikil Wale United States 5 119 0.7× 113 0.9× 132 1.2× 27 0.5× 7 0.3× 7 267

Countries citing papers authored by José Ignacio Abreu

Since Specialization
Citations

This map shows the geographic impact of José Ignacio Abreu'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 José Ignacio Abreu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Ignacio Abreu more than expected).

Fields of papers citing papers by José Ignacio Abreu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Ignacio Abreu. 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 José Ignacio Abreu. The network helps show where José Ignacio Abreu may publish in the future.

Co-authorship network of co-authors of José Ignacio Abreu

This figure shows the co-authorship network connecting the top 25 collaborators of José Ignacio Abreu. A scholar is included among the top collaborators of José Ignacio Abreu 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 José Ignacio Abreu. José Ignacio Abreu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Abreu, José Ignacio, et al.. (2024). A comprehensive methodology to construct standardised datasets for Science and Technology Parks. Data & Knowledge Engineering. 153. 102338–102338.
2.
Abreu, José Ignacio, et al.. (2023). Multidimensional Data Analysis for Enhancing In-Depth Knowledge on the Characteristics of Science and Technology Parks. Applied Sciences. 13(23). 12595–12595. 1 indexed citations
3.
Abreu, José Ignacio, et al.. (2023). A Review of Research-based Automatic Text Simplification Tools. Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante). 321–330. 1 indexed citations
4.
Abreu, José Ignacio, et al.. (2023). A Review of Parallel Corpora for Automatic Text Simplification. Key Challenges Moving Forward. Lecture notes in computer science. 62–78.
5.
Abreu, José Ignacio, et al.. (2021). Boosting Perturbation-Based Iterative Algorithms to Compute the Median String. IEEE Access. 9. 169299–169308.
6.
Abreu, José Ignacio, et al.. (2020). Multi-edition approach for Median String Problem. 14. 1–6. 1 indexed citations
7.
Garcés, Hugo O., et al.. (2017). Energy Efficiency Monitoring in a Coal Boiler Based on Optical Variables and Artificial Intelligence. IFAC-PapersOnLine. 50(1). 13904–13909. 6 indexed citations
8.
Gutiérrez, Yoan, et al.. (2013). UMCC_DLSI: Semantic and Lexical features for detection and classification Drugs in biomedical texts. Joint Conference on Lexical and Computational Semantics. 636–643. 3 indexed citations
9.
Gutiérrez, Yoan, et al.. (2013). UMCC_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance. Joint Conference on Lexical and Computational Semantics. 93–97. 1 indexed citations
10.
Gutiérrez, Yoan, et al.. (2013). UMCC_DLSI-(SA): Using a ranking algorithm and informal features to solve Sentiment Analysis in Twitter. Joint Conference on Lexical and Computational Semantics. 443–449. 3 indexed citations
11.
Gutiérrez, Yoan, et al.. (2013). UMCC_DLSI: Textual Similarity based on Lexical-Semantic features. Joint Conference on Lexical and Computational Semantics. 1. 109–118. 1 indexed citations
12.
Gutiérrez, Yoan, et al.. (2013). UMCC_DLSI: Reinforcing a Ranking Algorithm with Sense Frequencies and Multidimensional Semantic Resources to solve Multilingual Word Sense Disambiguation. Joint Conference on Lexical and Computational Semantics. 2. 241–249. 12 indexed citations
13.
14.
Fernández, Michael, Leyden Fernández, José Ignacio Abreu, & Miguel Garriga. (2008). Classification of voltage-gated K+ ion channels from 3D pseudo-folding graph representation of protein sequences using genetic algorithm-optimized support vector machines. Journal of Molecular Graphics and Modelling. 26(8). 1306–1314. 3 indexed citations
15.
Fernández, Michael, et al.. (2007). Classification of conformational stability of protein mutants from 3D pseudo‐folding graph representation of protein sequences using support vector machines. Proteins Structure Function and Bioinformatics. 70(1). 167–175. 21 indexed citations
16.
Fernández, Leyden, Julio Caballero, José Ignacio Abreu, & Michael Fernández. (2007). Amino acid sequence autocorrelation vectors and bayesian‐regularized genetic neural networks for modeling protein conformational stability: Gene V protein mutants. Proteins Structure Function and Bioinformatics. 67(4). 834–852. 47 indexed citations
17.
Fernández, Michael, Julio Caballero, Leyden Fernández, José Ignacio Abreu, & Miguel Garriga. (2007). Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: Chymotrypsin inhibitor 2 mutants. Journal of Molecular Graphics and Modelling. 26(4). 748–759. 18 indexed citations
18.
Fernández, Michael, et al.. (2007). Classification of conformational stability of protein mutants from 2D graph representation of protein sequences using support vector machines. Molecular Simulation. 33(11). 889–896. 4 indexed citations
19.
Caballero, Julio, Leyden Fernández, Miguel Garriga, et al.. (2006). Proteometric study of ghrelin receptor function variations upon mutations using amino acid sequence autocorrelation vectors and genetic algorithm-based least square support vector machines. Journal of Molecular Graphics and Modelling. 26(1). 166–178. 56 indexed citations
20.
Caballero, Julio, Leyden Fernández, José Ignacio Abreu, & Michael Fernández. (2006). Amino Acid Sequence Autocorrelation Vectors and Ensembles of Bayesian‐Regularized Genetic Neural Networks for Prediction of Conformational Stability of Human Lysozyme Mutants.. ChemInform. 37(31). 1 indexed citations

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.

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