José Ignacio Abreu

508 citations
35 papers · 391 indexed · h-index 9
Topics
Protein Structure and Dynamics (8 papers)Machine Learning in Bioinformatics (7 papers)Computational Drug Discovery Methods (7 papers)
Partner nations
CubaSpainChile

In The Last Decade

José Ignacio Abreu

30 papers receiving 383 citations

Peers

José Ignacio Abreu
Comparison fields: 5 of 81
  • Molecular Biology 161
  • Artificial Intelligence 129
  • Computational Theory and Mathematics 108
  • Materials Chemistry 59
  • Organic Chemistry 27
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Citations per field
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Citations per year

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
#WorkIndexed citations
1 0
2 1
3 1
4 0
5 0
6 1
7 6
8
UMCC_DLSI: Semantic and Lexical features for detection and classification Drugs in biomedical texts
3
9
UMCC_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance
1
10
UMCC_DLSI-(SA): Using a ranking algorithm and informal features to solve Sentiment Analysis in Twitter
3
11
UMCC_DLSI: Textual Similarity based on Lexical-Semantic features
1
12
UMCC_DLSI: Reinforcing a Ranking Algorithm with Sense Frequencies and Multidimensional Semantic Resources to solve Multilingual Word Sense Disambiguation
12
13 4
14 3
15 21
16 47
17 18
18 4
19 56
20 1

About José Ignacio Abreu

José Ignacio Abreu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Hardware and Architecture, having authored 35 papers that have together received 391 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Machine Learning in Bioinformatics (7 papers) and Computational Drug Discovery Methods (7 papers). The work is most often cited by research in Computational Theory and Mathematics (108 citations), Artificial Intelligence (129 citations) and Molecular Biology (161 citations). José Ignacio Abreu has collaborated with scholars based in Cuba, Spain and Chile. Frequent 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. Their work appears in journals such as IEEE Access, Proteins Structure Function and Bioinformatics and Applied Soft Computing.

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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