J. Jesús Naveja
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Infectious Diseases top 10%
- Pharmacology top 10%
- Oncology
- Co-authors
- José L. Medina‐FrancoEdgar López‐LópezArmando González-DíazCarlos A. Aguilar‐SalinasNeftalí Eduardo Antonio-VillaOmar Yaxmehen Bello‐ChavollaAlejandro Márquez‐SalinasArsenio Vargas‐Vázquez
- Topics
- Computational Drug Discovery Methods (20 papers)Protein Degradation and Inhibitors (6 papers)Microbial Natural Products and Biosynthesis (5 papers)
- Partner nations
- MexicoGermanyUnited States
In The Last Decade
J. Jesús Naveja
41 papers receiving 937 citations
Peers
Comparison fields: 5 of 119
- Computational Theory and Mathematics 390
- Molecular Biology 360
- Infectious Diseases 237
- Pharmacology 127
- Oncology 119
Countries citing papers authored by J. Jesús Naveja
This map shows the geographic impact of J. Jesús Naveja'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 J. Jesús Naveja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Jesús Naveja more than expected).
Fields of papers citing papers by J. Jesús Naveja
This network shows the impact of papers produced by J. Jesús Naveja. 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 J. Jesús Naveja. The network helps show where J. Jesús Naveja may publish in the future.
Co-authorship network of co-authors of J. Jesús Naveja
This figure shows the co-authorship network connecting the top 25 collaborators of J. Jesús Naveja. A scholar is included among the top collaborators of J. Jesús Naveja 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 J. Jesús Naveja. J. Jesús Naveja 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 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 277 | |
| 6 | 23 | |
| 7 | 9 | |
| 8 | 66 | |
| 9 | 29 | |
| 10 | 38 | |
| 11 | 18 | |
| 12 | 5 | |
| 13 | 8 | |
| 14 | 36 | |
| 15 | 12 | |
| 16 | 26 | |
| 17 | 8 | |
| 18 | Review. One Drug for Multiple Targets: A Computational Perspective | 18 |
| 19 | 7 | |
| 20 | 16 |
About J. Jesús Naveja
J. Jesús Naveja is a scholar working on Computational Theory and Mathematics, Pharmacology and Gender Studies, having authored 42 papers that have together received 952 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (20 papers), Protein Degradation and Inhibitors (6 papers) and Microbial Natural Products and Biosynthesis (5 papers). The work is most often cited by research in Computational Theory and Mathematics (390 citations), Infectious Diseases (237 citations) and Pharmacology (127 citations). J. Jesús Naveja has collaborated with scholars based in Mexico, Germany and United States. Frequent co-authors include José L. Medina‐Franco, Edgar López‐López, Armando González-Díaz, Carlos A. Aguilar‐Salinas, Neftalí Eduardo Antonio-Villa, Omar Yaxmehen Bello‐Chavolla, Alejandro Márquez‐Salinas, Arsenio Vargas‐Vázquez, Jessica Paola Bahena-López and Carlos A. Fermín‐Martínez. Their work appears in journals such as Nature Genetics, Bioinformatics and The Journal of Clinical Endocrinology & Metabolism.
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.