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Plant Reproduction
|
November 9, 2013
Polyploids as a "model system" for the study of heterosis
Jacob D Washburn, James A Birchler
The New Phytologist
|
February 13, 2024
Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations
Alper Adak, Seth C Murray, Jacob D Washburn
TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik
|
June 2, 2025
Improving plant breeding through AI-supported data integration
Worasit Sangjan, Daniel R Kick, Jacob D Washburn
Journal of Experimental Botany
|
April 27, 2023
Enhancing the resilience of plant systems to climate change
David M Braun, Jacob D Washburn, Jeffrey D Wood
Journal of Genetics and Genomics = Yi Chuan Xue Bao
|
August 25, 2019
Progressive heterosis in genetically defined tetraploid maize
Jacob D Washburn, Mitchell J McElfresh, James A Birchler
American Journal of Botany
|
September 17, 2015
Phylogeny and photosynthesis of the grass tribe Paniceae
Jacob D Washburn, James C Schnable, Gerrit Davidse, et al.
Molecular Breeding : New Strategies in Plant Improvement
|
January 15, 2013
Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population
Jacob D Washburn, Seth C Murray, Byron L Burson, et al.
Journal of Economic Entomology
|
October 10, 2023
GWAS analysis of maize host plant resistance to western corn rootworm (Coleoptera: Chrysomelidae) reveals candidate small effect loci for resistance breeding
Jacob D Washburn, Harper F LaFond, Martian C Lapadatescu, et al.
Seminars in Cell & Developmental Biology
|
March 8, 2013
Watching the grin fade: tracing the effects of polyploidy on different evolutionary time scales
Dustin Mayfield-Jones, Jacob D Washburn, Tatiana Arias, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
March 8, 2019
Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence
Jacob D Washburn, Maria Katherine Mejia-Guerra, Guillaume Ramstein, et al.
Page
of 4
Search research articles
Search
Showing results (1-10 of 31) with videos related to
Sort By:
Page
of 4
Plant Reproduction
|
November 9, 2013
Polyploids as a "model system" for the study of heterosis
Jacob D Washburn, James A Birchler
The New Phytologist
|
February 13, 2024
Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations
Alper Adak, Seth C Murray, Jacob D Washburn
TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik
|
June 2, 2025
Improving plant breeding through AI-supported data integration
Worasit Sangjan, Daniel R Kick, Jacob D Washburn
Journal of Experimental Botany
|
April 27, 2023
Enhancing the resilience of plant systems to climate change
David M Braun, Jacob D Washburn, Jeffrey D Wood
Journal of Genetics and Genomics = Yi Chuan Xue Bao
|
August 25, 2019
Progressive heterosis in genetically defined tetraploid maize
Jacob D Washburn, Mitchell J McElfresh, James A Birchler
American Journal of Botany
|
September 17, 2015
Phylogeny and photosynthesis of the grass tribe Paniceae
Jacob D Washburn, James C Schnable, Gerrit Davidse, et al.
Molecular Breeding : New Strategies in Plant Improvement
|
January 15, 2013
Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population
Jacob D Washburn, Seth C Murray, Byron L Burson, et al.
Journal of Economic Entomology
|
October 10, 2023
GWAS analysis of maize host plant resistance to western corn rootworm (Coleoptera: Chrysomelidae) reveals candidate small effect loci for resistance breeding
Jacob D Washburn, Harper F LaFond, Martian C Lapadatescu, et al.
Seminars in Cell & Developmental Biology
|
March 8, 2013
Watching the grin fade: tracing the effects of polyploidy on different evolutionary time scales
Dustin Mayfield-Jones, Jacob D Washburn, Tatiana Arias, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
March 8, 2019
Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence
Jacob D Washburn, Maria Katherine Mejia-Guerra, Guillaume Ramstein, et al.
Page
of 4