Juan A. Castillo‐Garit
- Computational Theory and Mathematics top 0.5%
- Molecular Biology
- Organic Chemistry top 10%
- Spectroscopy top 5%
- Materials Chemistry
- Co-authors
- Yovani Marrero‐PonceFrancisco TorrensGerardo M. Casañola‐MartínHuong Le‐Thi‐ThuHai Pham‐TheRamón García‐DomenechRichard RotondoEduardo A. Castro
- Topics
- Computational Drug Discovery Methods (47 papers)Analytical Chemistry and Chromatography (8 papers)Machine Learning in Bioinformatics (7 papers)
In The Last Decade
Juan A. Castillo‐Garit
60 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 102
- Computational Theory and Mathematics 742
- Molecular Biology 549
- Organic Chemistry 291
- Spectroscopy 188
- Materials Chemistry 128
Countries citing papers authored by Juan A. Castillo‐Garit
This map shows the geographic impact of Juan A. Castillo‐Garit'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 Juan A. Castillo‐Garit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan A. Castillo‐Garit more than expected).
Fields of papers citing papers by Juan A. Castillo‐Garit
This network shows the impact of papers produced by Juan A. Castillo‐Garit. 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 Juan A. Castillo‐Garit. The network helps show where Juan A. Castillo‐Garit may publish in the future.
Co-authorship network of co-authors of Juan A. Castillo‐Garit
This figure shows the co-authorship network connecting the top 25 collaborators of Juan A. Castillo‐Garit. A scholar is included among the top collaborators of Juan A. Castillo‐Garit 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 Juan A. Castillo‐Garit. Juan A. Castillo‐Garit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 5 | |
| 11 | 8 | |
| 12 | 57 | |
| 13 | 12 | |
| 14 | 33 | |
| 15 | 19 | |
| 16 | 54 | |
| 17 | Atom-based 3D-chiral quadratic indices. Part 3: prediction of the binding affinity of the stereoisomers of fenoterolto the β2 adrenergic receptor | 1 |
| 18 | 68 | |
| 19 | 37 | |
| 20 | 74 |
About Juan A. Castillo‐Garit
Juan A. Castillo‐Garit is a scholar working on Computational Theory and Mathematics, Pharmaceutical Science and Spectroscopy, having authored 66 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (47 papers), Analytical Chemistry and Chromatography (8 papers) and Machine Learning in Bioinformatics (7 papers). The work is most often cited by research in Computational Theory and Mathematics (742 citations), Toxicology (40 citations) and Spectroscopy (188 citations). Juan A. Castillo‐Garit has collaborated with scholars based in Spain, Cuba and Vietnam. Frequent co-authors include Yovani Marrero‐Ponce, Francisco Torrens, Gerardo M. Casañola‐Martín, Huong Le‐Thi‐Thu, Hai Pham‐The, Ramón García‐Domenech, Richard Rotondo, Eduardo A. Castro, Stephen J. Barigye and Concepción Abad. Their work appears in journals such as Chemosphere, Chemical Physics Letters and Molecules.
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.