Joseph M. Paggi
- Molecular Biology top 1%
- Plant Science top 0.5%
- Genetics top 2%
- Cancer Research top 2%
- Immunology top 5%
- Co-authors
- Steven L. SalzbergChristopher BennettDaehwan KimChanhee ParkRon O. DrorBrian K. KobilkaNaomi R. LatorracaQianhui Qu
- Topics
- Neuropeptides and Animal Physiology (5 papers)RNA and protein synthesis mechanisms (5 papers)RNA modifications and cancer (4 papers)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Joseph M. Paggi
16 papers receiving 9.0k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Molecular Biology 5.5k
- Plant Science 2.6k
- Genetics 1.1k
- Cancer Research 802
- Immunology 768
Countries citing papers authored by Joseph M. Paggi
This map shows the geographic impact of Joseph M. Paggi'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 Joseph M. Paggi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph M. Paggi more than expected).
Fields of papers citing papers by Joseph M. Paggi
This network shows the impact of papers produced by Joseph M. Paggi. 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 Joseph M. Paggi. The network helps show where Joseph M. Paggi may publish in the future.
Co-authorship network of co-authors of Joseph M. Paggi
This figure shows the co-authorship network connecting the top 25 collaborators of Joseph M. Paggi. A scholar is included among the top collaborators of Joseph M. Paggi 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 Joseph M. Paggi. Joseph M. Paggi 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 | 10 | |
| 3 | The Art and Science of Molecular Dockingbreakdown → | 143 |
| 4 | 25 | |
| 5 | 56 | |
| 6 | 72 | |
| 7 | 21 | |
| 8 | 84 | |
| 9 | Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotypebreakdown → | 7900 |
| 10 | 36 | |
| 11 | 60 | |
| 12 | 42 | |
| 13 | 12 | |
| 14 | Structure of the µ-opioid receptor–Gi protein complexbreakdown → | 495 |
| 15 | 76 | |
| 16 | 27 | |
| 17 | Behaviour of rifaximin in foam formulation after intrauterine administration. | 2 |
About Joseph M. Paggi
Joseph M. Paggi is a scholar working on Cellular and Molecular Neuroscience, Computational Theory and Mathematics and Molecular Biology, having authored 17 papers that have together received 9.1k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (5 papers), RNA and protein synthesis mechanisms (5 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Molecular Biology (5.5k citations), Plant Science (2.6k citations) and Horticulture (56 citations). Joseph M. Paggi has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Steven L. Salzberg, Christopher Bennett, Daehwan Kim, Chanhee Park, Ron O. Dror, Brian K. Kobilka, Naomi R. Latorraca, Qianhui Qu, Georgios Skiniotis and Daniel Hilger. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.
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.