Charles L. Webber
- Cognitive Neuroscience top 2%
- Statistical and Nonlinear Physics top 1%
- Plant Science top 5%
- Economics and Econometrics top 2%
- Molecular Biology
- Co-authors
- Joseph P. ZbilutAlessandro GiulianiNitza ThomassonNorbert MarwanAlfredo ColosimoPaul M. WhiteJames W. ShreflerKevin Shockley
- Topics
- Weed Control and Herbicide Applications (23 papers)Chaos control and synchronization (15 papers)Hibiscus Plant Research Studies (14 papers)
- Partner nations
- United StatesItalyGermany
In The Last Decade
Charles L. Webber
125 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Cognitive Neuroscience 696
- Statistical and Nonlinear Physics 658
- Plant Science 569
- Economics and Econometrics 566
- Molecular Biology 541
Countries citing papers authored by Charles L. Webber
This map shows the geographic impact of Charles L. Webber'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 Charles L. Webber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charles L. Webber more than expected).
Fields of papers citing papers by Charles L. Webber
This network shows the impact of papers produced by Charles L. Webber. 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 Charles L. Webber. The network helps show where Charles L. Webber may publish in the future.
Co-authorship network of co-authors of Charles L. Webber
This figure shows the co-authorship network connecting the top 25 collaborators of Charles L. Webber. A scholar is included among the top collaborators of Charles L. Webber 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 Charles L. Webber. Charles L. Webber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Recurrence Plots and Their Quantifications: Expanding Horizons : Proceedings of the 6th International Symposium on Recurrence Plots, Grenoble, France, 17-19 June 2015 | 1 |
| 2 | 74 | |
| 3 | 7 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 17 | |
| 7 | 45 | |
| 8 | Pelargonic acid - a potential organic aquatic herbicide for duckweed management | 2 |
| 9 | 18 | |
| 10 | 0 | |
| 11 | 9 | |
| 12 | 39 | |
| 13 | 41 | |
| 14 | 37 | |
| 15 | Application of Recurrence Quantification Analysis to EEG Signals. | 12 |
| 16 | 28 | |
| 17 | 37 | |
| 18 | 27 | |
| 19 | 11 | |
| 20 | 17 |
About Charles L. Webber
Charles L. Webber is a scholar working on Pharmacology, Agronomy and Crop Science and Statistical and Nonlinear Physics, having authored 127 papers that have together received 3.8k indexed citations. Recurring topics across this work include Weed Control and Herbicide Applications (23 papers), Chaos control and synchronization (15 papers) and Hibiscus Plant Research Studies (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (658 citations), Cognitive Neuroscience (696 citations) and Pharmacology (225 citations). Charles L. Webber has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Joseph P. Zbilut, Alessandro Giuliani, Nitza Thomasson, Norbert Marwan, Alfredo Colosimo, Paul M. White, James W. Shrefler, Kevin Shockley, Dexter F. Speck and K. Pleschka. Their work appears in journals such as Chemical Reviews, PLoS ONE and Journal of Agricultural and Food Chemistry.
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.