Judith E. Dayhoff
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
-
- Scheduling and Optimization Algorithms
Papers in ⓘ
-
- Neural Networks and Applications 17
- Neural Networks and Reservoir Computing 3
-
- Neural dynamics and brain function 9
- Co-authors
- J.M. DeLeo (2 shared papers)G. L. Gerstein (2 shared papers)Stuart R. Hameroff (8 shared papers)Rafael Lahoz-Beltrá (8 shared papers)Daw-Tung Lin (7 shared papers)Panos A. Ligomenides (6 shared papers)Anna R. Panchenko (1 shared paper)Stephen H. Bryant (1 shared paper)
- Journals
- Journal of Neurophysiology (2 papers)Bulletin of Mathematical Biology (2 papers)Cancer (1 paper)Neurocomputing (1 paper)Mathematical and Computer Modelling (1 paper)
- Partner nations
- United StatesSpainSweden
In The Last Decade
Judith E. Dayhoff
38 papers receiving 818 citations
Peers
Comparison fields: 5 of 156
- Cognitive Neuroscience 166
- Industrial and Manufacturing Engineering 76
- Cellular and Molecular Neuroscience 127
- Artificial Intelligence 213
- Health Informatics 7
Countries citing papers authored by Judith E. Dayhoff
This map shows the geographic impact of Judith E. Dayhoff'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 Judith E. Dayhoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Judith E. Dayhoff more than expected).
Fields of papers citing papers by Judith E. Dayhoff
This network shows the impact of papers produced by Judith E. Dayhoff. 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 Judith E. Dayhoff. The network helps show where Judith E. Dayhoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Judith E. Dayhoff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 321 | |
| 2 | 1983 | 84 | |
| 3 | 1983 | 70 | |
| 4 | 2009 | 59 | |
| 5 | 1995 | 41 | |
| 6 | 1993 | 37 | |
| 7 | 1992 | 32 | |
| 8 | 1986 | 30 | |
| 9 | 1994 | 27 | |
| 10 | 1992 | 24 | |
| 11 | 1986 | 22 | |
| 12 | 2001 | 20 | |
| 13 | 1987 | 14 | |
| 14 | 1984 | 12 | |
| 15 | 2001 | 8 | |
| 16 | 1984 | 8 | |
| 17 | 1990 | 6 | |
| 18 | A Learning Algorithm for Adaptive Time-Delays in a Temporal Neural Network | 1992 | 6 |
| 19 | 1990 | 5 | |
| 20 | 2002 | 5 |
About Judith E. Dayhoff
Judith E. Dayhoff is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Electrical and Electronic Engineering, Molecular Biology and Cell Biology, having authored 43 papers that have together received 880 indexed citations. Recurring topics across this work include Neural Networks and Applications (17 papers), Neural dynamics and brain function (9 papers), Advanced Memory and Neural Computing (5 papers), Microtubule and mitosis dynamics (4 papers), Neural Networks and Reservoir Computing (3 papers), Scheduling and Optimization Algorithms (3 papers), Fractal and DNA sequence analysis (3 papers) and Neuroscience and Neural Engineering (2 papers). The work is most often cited by research in Cognitive Neuroscience (166 citations), Industrial and Manufacturing Engineering (76 citations), Cellular and Molecular Neuroscience (127 citations), Artificial Intelligence (213 citations) and Health Informatics (7 citations). Judith E. Dayhoff has collaborated with scholars based in United States, Spain and Sweden. Frequent co-authors include J.M. DeLeo, G. L. Gerstein, Stuart R. Hameroff, Rafael Lahoz-Beltrá, Daw-Tung Lin, Panos A. Ligomenides, Anna R. Panchenko, Stephen H. Bryant, Benjamin A. Shoemaker and Charlese E Swenberg. Their work appears in journals such as Journal of Neurophysiology, Bulletin of Mathematical Biology, Cancer, Neurocomputing and Mathematical and Computer Modelling.
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.