Gustavo Pacheco–Rodriguez
- Molecular Biology top 10%
- Physiology top 5%
- Cell Biology top 2%
- Oncology top 10%
- Pulmonary and Respiratory Medicine top 10%
- Co-authors
- Joel MossMartha VaughanThomas N. DarlingAngelo M. Taveira‐DaSilvaWendy K. SteagallRonald AdamikVictor J. FerransJianwu Wang
- Topics
- Tuberous Sclerosis Complex Research (30 papers)Cellular transport and secretion (15 papers)Calcium signaling and nucleotide metabolism (11 papers)
- Cited by
- PhysiologyCell Biology
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryThe Journal of Experimental Medicine
- Partner nations
- United StatesNetherlandsItaly
In The Last Decade
Gustavo Pacheco–Rodriguez
63 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 895
- Physiology 711
- Cell Biology 546
- Oncology 446
- Pulmonary and Respiratory Medicine 312
Countries citing papers authored by Gustavo Pacheco–Rodriguez
This map shows the geographic impact of Gustavo Pacheco–Rodriguez'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 Gustavo Pacheco–Rodriguez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gustavo Pacheco–Rodriguez more than expected).
Fields of papers citing papers by Gustavo Pacheco–Rodriguez
This network shows the impact of papers produced by Gustavo Pacheco–Rodriguez. 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 Gustavo Pacheco–Rodriguez. The network helps show where Gustavo Pacheco–Rodriguez may publish in the future.
Co-authorship network of co-authors of Gustavo Pacheco–Rodriguez
This figure shows the co-authorship network connecting the top 25 collaborators of Gustavo Pacheco–Rodriguez. A scholar is included among the top collaborators of Gustavo Pacheco–Rodriguez 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 Gustavo Pacheco–Rodriguez. Gustavo Pacheco–Rodriguez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 12 | |
| 5 | 15 | |
| 6 | 14 | |
| 7 | 28 | |
| 8 | 27 | |
| 9 | 46 | |
| 10 | 13 | |
| 11 | 45 | |
| 12 | 19 | |
| 13 | 14 | |
| 14 | 85 | |
| 15 | 76 | |
| 16 | 4 | |
| 17 | 36 | |
| 18 | 6 | |
| 19 | 17 | |
| 20 | 2 |
About Gustavo Pacheco–Rodriguez
Gustavo Pacheco–Rodriguez is a scholar working on Physiology, Physiology and Cell Biology, having authored 64 papers that have together received 2.0k indexed citations. Recurring topics across this work include Tuberous Sclerosis Complex Research (30 papers), Cellular transport and secretion (15 papers) and Calcium signaling and nucleotide metabolism (11 papers). The work is most often cited by research in Physiology (187 citations), Cell Biology (546 citations) and Physiology (711 citations). Gustavo Pacheco–Rodriguez has collaborated with scholars based in United States, Netherlands and Italy. Frequent co-authors include Joel Moss, Martha Vaughan, Thomas N. Darling, Angelo M. Taveira‐DaSilva, Wendy K. Steagall, Ronald Adamik, Victor J. Ferrans, Jianwu Wang, J. Philip McCoy and Kazuyo Takeda. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.
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.