James A. Anderson
Affiliations: | Psychology | Brown University, Providence, RI |
Area:
Computational modeling, artificial intelligenceWebsite:
http://psych.brown.edu/people/facultypage.php?id=1106970154Google:
"James Anderson"Mean distance: 15.91 (cluster 15)
Children
Sign in to add trainee| Richard Golden | grad student | Brown | |
| Alan Kawamoto | grad student | 1985 | Brown |
| Mark G. McNellis | grad student | 2000 | Brown |
BETA: Related publications
See more...
Publications
|
You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect. |
| Negash T, Edae EA, Tilahun L, et al. (2022) Genome-wide association mapping for field and seedling resistance to the emerging Puccinia graminis f. sp. tritici race TTRTF in wheat. The Plant Genome. e20274 |
| Rauf Y, Bajgain P, Rouse M, et al. (2021) Molecular Characterization of Genomic Regions for Adult Plant Resistance to Stem Rust in a Spring Wheat Mapping Population. Plant Disease |
| Sallam AH, Manan F, Bajgain P, et al. (2020) Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat. The Plant Genome. 13: e20051 |
| Bajgain P, Zhang X, Anderson JA. (2020) Dominance and G×E interaction effects improve genomic prediction and genetic gain in intermediate wheatgrass (Thinopyrum intermedium). The Plant Genome. 13: e20012 |
| Kolmer J, Turner MK, Rouse MN, et al. (2020) Adult plant leaf rust resistance in AC Taber wheat maps to chromosomes 2BS and 3BS. Phytopathology |
| Sallam AH, Conley E, Prakapenka D, et al. (2020) Improving Prediction Accuracy Using Multi-allelic Haplotype Prediction and Training Population Optimization in Wheat. G3 (Bethesda, Md.) |
| Crain J, Bajgain P, Anderson J, et al. (2020) Enhancing Crop Domestication Through Genomic Selection, a Case Study of Intermediate Wheatgrass. Frontiers in Plant Science. 11: 319 |
| Adeyemo E, Bajgain P, Conley E, et al. (2020) Optimizing Training Population Size and Content to Improve Prediction Accuracy of FHB-Related Traits in Wheat Agronomy. 10: 543 |
| Moghimi A, Yang C, Anderson JA. (2020) Aerial hyperspectral imagery and deep neural networks for high-throughput yield phenotyping in wheat Computers and Electronics in Agriculture. 172: 105299 |
| Harman J, Loes A, Anderson JA, et al. (2020) S100A9S Evolved Potent Proinflammatory Activity and Lost Proteolytic Resistance from a Proteolytically Resistant, Weakly Proinflammatory Ancestor Biophysical Journal. 118: 338a |