Scotland Leman
- Plant Science top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Molecular Biology
- Cell Biology top 10%
- Co-authors
- Leanna HouseChris NorthBoris A. VinatzerAlex EndertRongman CaiChristopher R. ClarkeChao HanShuangchun Yan
- Topics
- Data Visualization and Analytics (13 papers)Data Analysis with R (9 papers)Plant-Microbe Interactions and Immunity (5 papers)
- Partner nations
- United StatesFranceBrazil
In The Last Decade
Scotland Leman
47 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 116
- Plant Science 536
- Computer Vision and Pattern Recognition 346
- Artificial Intelligence 245
- Molecular Biology 146
- Cell Biology 112
Countries citing papers authored by Scotland Leman
This map shows the geographic impact of Scotland Leman'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 Scotland Leman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scotland Leman more than expected).
Fields of papers citing papers by Scotland Leman
This network shows the impact of papers produced by Scotland Leman. 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 Scotland Leman. The network helps show where Scotland Leman may publish in the future.
Co-authorship network of co-authors of Scotland Leman
This figure shows the co-authorship network connecting the top 25 collaborators of Scotland Leman. A scholar is included among the top collaborators of Scotland Leman 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 Scotland Leman. Scotland Leman 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 | Bringing interactive visual analytics to the classroom for developing EDA skills | 4 |
| 3 | 19 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 11 | |
| 8 | A Time Varying Parameter State-Space Model for Analyzing Money Supply-Economic Growth Nexus | 3 |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 30 | |
| 12 | 28 | |
| 13 | 33 | |
| 14 | 14 | |
| 15 | 22 | |
| 16 | 35 | |
| 17 | 147 | |
| 18 | 28 | |
| 19 | 1 | |
| 20 | 13 |
About Scotland Leman
Scotland Leman is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Ecological Modeling, having authored 52 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Visualization and Analytics (13 papers), Data Analysis with R (9 papers) and Plant-Microbe Interactions and Immunity (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (346 citations), Plant Science (536 citations) and Signal Processing (93 citations). Scotland Leman has collaborated with scholars based in United States, France and Brazil. Frequent co-authors include Leanna House, Chris North, Boris A. Vinatzer, Alex Endert, Rongman Cai, Christopher R. Clarke, Chao Han, Shuangchun Yan, John Wenskovitch and Nalvo F. Almeida. Their work appears in journals such as Journal of the American Statistical Association, Bioinformatics and PLoS ONE.
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.