Lesley A. Schimanski
- Statistics, Probability and Uncertainty top 1%
- Cellular and Molecular Neuroscience top 10%
- Cognitive Neuroscience top 10%
- Information Systems and Management top 5%
- Public Health, Environmental and Occupational Health
- Co-authors
- Meredith T. NilesJuan Pablo AlperínErin C. McKiernanPeter NguyenCarol Muñoz NievesLisa MatthiasCarol A. BarnesP. Lipa
- Topics
- Neuroscience and Neuropharmacology Research (11 papers)Memory and Neural Mechanisms (11 papers)scientometrics and bibliometrics research (5 papers)
- Cited by
- Statistics, Probability and UncertaintyInformation Systems and ManagementCellular and Molecular Neuroscience
- Partner nations
- United StatesCanadaMexico
In The Last Decade
Lesley A. Schimanski
16 papers receiving 743 citations
Peers
Comparison fields: 5 of 134
- Statistics, Probability and Uncertainty 209
- Cellular and Molecular Neuroscience 198
- Cognitive Neuroscience 176
- Information Systems and Management 105
- Public Health, Environmental and Occupational Health 83
Countries citing papers authored by Lesley A. Schimanski
This map shows the geographic impact of Lesley A. Schimanski'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 Lesley A. Schimanski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lesley A. Schimanski more than expected).
Fields of papers citing papers by Lesley A. Schimanski
This network shows the impact of papers produced by Lesley A. Schimanski. 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 Lesley A. Schimanski. The network helps show where Lesley A. Schimanski may publish in the future.
Co-authorship network of co-authors of Lesley A. Schimanski
This figure shows the co-authorship network connecting the top 25 collaborators of Lesley A. Schimanski. A scholar is included among the top collaborators of Lesley A. Schimanski 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 Lesley A. Schimanski. Lesley A. Schimanski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 18 | |
| 3 | 25 | |
| 4 | 130 | |
| 5 | 101 | |
| 6 | 189 | |
| 7 | 17 | |
| 8 | 34 | |
| 9 | 23 | |
| 10 | 32 | |
| 11 | 44 | |
| 12 | 30 | |
| 13 | 18 | |
| 14 | 18 | |
| 15 | 53 | |
| 16 | 37 |
About Lesley A. Schimanski
Lesley A. Schimanski is a scholar working on Statistics, Probability and Uncertainty, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 16 papers that have together received 774 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (11 papers), Memory and Neural Mechanisms (11 papers) and scientometrics and bibliometrics research (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (209 citations), Information Systems and Management (105 citations) and Cellular and Molecular Neuroscience (198 citations). Lesley A. Schimanski has collaborated with scholars based in United States, Canada and Mexico. Frequent co-authors include Meredith T. Niles, Juan Pablo Alperín, Erin C. McKiernan, Peter Nguyen, Carol Muñoz Nieves, Lisa Matthias, Carol A. Barnes, P. Lipa, Gustavo E. Fischman and Douglas Wahłsten. Their work appears in journals such as Journal of Neuroscience, PLoS ONE and Neuroscience & Biobehavioral Reviews.
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.