Shane T. Jensen
- Molecular Biology top 10%
- Genetics top 5%
- Ecology top 5%
- Plant Science top 10%
- Infectious Diseases top 10%
- Co-authors
- Jun S. LiuPatrick EichenbergerMasaya FujitaRichard LosickJosé Eduardo González‐PastorVirginie MolleErin M. ConlonMolly Megraw
- Topics
- Gene expression and cancer classification (6 papers)Sports Analytics and Performance (4 papers)Optimal Experimental Design Methods (4 papers)
- Cited by
- GeneticsEcologyMolecular Biology
- Partner nations
- United StatesFranceGreece
In The Last Decade
Shane T. Jensen
25 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 138
- Molecular Biology 1.1k
- Genetics 675
- Ecology 449
- Plant Science 246
- Infectious Diseases 120
Countries citing papers authored by Shane T. Jensen
This map shows the geographic impact of Shane T. Jensen'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 Shane T. Jensen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane T. Jensen more than expected).
Fields of papers citing papers by Shane T. Jensen
This network shows the impact of papers produced by Shane T. Jensen. 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 Shane T. Jensen. The network helps show where Shane T. Jensen may publish in the future.
Co-authorship network of co-authors of Shane T. Jensen
This figure shows the co-authorship network connecting the top 25 collaborators of Shane T. Jensen. A scholar is included among the top collaborators of Shane T. Jensen 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 Shane T. Jensen. Shane T. Jensen 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 | 3 | |
| 3 | 2 | |
| 4 | 84 | |
| 5 | Variable Selection Inference for Bayesian Additive Regression Trees | 3 |
| 6 | 81 | |
| 7 | 2 | |
| 8 | 26 | |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 42 | |
| 12 | 3 | |
| 13 | A spatially varying two-sample recombinant coalescent, with applications to HIV escape response. | 5 |
| 14 | 1 | |
| 15 | 148 | |
| 16 | 26 | |
| 17 | 68 | |
| 18 | 287 | |
| 19 | 198 | |
| 20 | 439 |
About Shane T. Jensen
Shane T. Jensen is a scholar working on Virology, Management Science and Operations Research and Statistics and Probability, having authored 27 papers that have together received 1.6k indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Sports Analytics and Performance (4 papers) and Optimal Experimental Design Methods (4 papers). The work is most often cited by research in Genetics (675 citations), Ecology (449 citations) and Molecular Biology (1.1k citations). Shane T. Jensen has collaborated with scholars based in United States, France and Greece. Frequent co-authors include Jun S. Liu, Patrick Eichenberger, Masaya Fujita, Richard Losick, José Eduardo González‐Pastor, Virginie Molle, Erin M. Conlon, Molly Megraw, Artemis G. Hatzigeorgiou and Koki Haga. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Journal of Molecular Biology.
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.