Buckler, Edward S.

Association mapping: critical considerations shift from genotyping to experimental design

Myles, S., Peiffer, J., Brown, P. J., Ersoz, E. S., Zhang, Z., Costich, D. E., & Buckler, E. S. (2009) · The Plant Cell

Genetic Mapping and Diversity in Plants and AnimalsGenetic Associations and Epidemiology

Cited by 857

Natural Variation in Maize Aphid Resistance Is Associated with 2,4-Dihydroxy-7-Methoxy-1,4-Benzoxazin-3-One Glucoside Methyltransferase Activity

Meihls, L. N., Handrick, V., Glauser, G., Barbier, H., Kaur, H., Haribal, M. M., Lipka, A. E., Gershenzon, J., Buckler, E. S., Erb, M., et al. (2013) · The Plant Cell

Insect-Plant Interactions and ControlGenetic Mapping and Diversity in Plants and Animals

Cited by 292

Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs

Zhang, X., Pérez-Rodríguez, P., Semagn, K., Beyene, Y., Babu, R., López-Cruz, M. A., San Vicente, F., Olsen, M., Buckler, E., Jannink, J.-L., et al. (2015) · Heredity

Genetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals

Cited by 212

Meiotic drive of chromosomal knobs reshaped the maize genome

Buckler, E. S., Phelps-Durr, T. L., Buckler, C. S. K., Dawe, R. K., Doebley, J. F., & Holtsford, T. P. (1999) · Genetics

Chromosomal and Genetic VariationsEvolution and Genetic Dynamics

Cited by 193

Breaking the curse of dimensionality to identify causal variants in Breeding 4

Ramstein, G. P., Jensen, S. E., & Buckler, E. S. (2019) · Theoretical and Applied Genetics

Genetic Mapping and Diversity in Plants and AnimalsGenetic and phenotypic traits in livestock

Cited by 87

Utility of climatic information via combining ability models to improve genomic prediction for yield within the genomes to fields maize project

Jarquin, D., de Leon, N., Romay, C., Bohn, M., Buckler, E. S., Ciampitti, I., Edwards, J., Ertl, D., Flint-Garcia, S., Gore, M. A., et al. (2021) · Frontiers in Genetics

Genetic and phenotypic traits in livestockGenetics and Plant Breeding

Cited by 86

Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets

McFarland, B. A., AlKhalifah, N., Bohn, M., Bubert, J., Buckler, E. S., Ciampitti, I., Edwards, J., Ertl, D., Gage, J. L., Falcon, C. M., et al. (2020) · BMC Research Notes

Genetics and Plant BreedingCrop Yield and Soil Fertility

Cited by 70

Predicting phenotypes from genetic, environment, management, and historical data using CNNs

Washburn, J. D., Cimen, E., Ramstein, G., Reeves, T., O’Briant, P., McLean, G., Cooper, M., Hammer, G., & Buckler, E. S. (2021) · Theoretical and Applied Genetics

Smart Agriculture and AIGenetic and phenotypic traits in livestock

Cited by 57

Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize

Ramstein, G. P., & Buckler, E. S. (2022) · Genome Biology

Genetic Mapping and Diversity in Plants and AnimalsGenomics and Phylogenetic Studies

Cited by 34

Modeling chromatin state from sequence across angiosperms using recurrent convolutional neural networks

Wrightsman, T., Marand, A. P., Crisp, P. A., Springer, N. M., & Buckler, E. S. (2021) · The Plant Genome

Genomics and Chromatin DynamicsPlant Molecular Biology Research

Cited by 17

A multiple alignment workflow shows the effect of repeat masking and parameter tuning on alignment in plants

Wu, Y., Johnson, L., Song, B., Romay, C., Stitzer, M., Siepel, A., Buckler, E., & Scheben, A. (2022) · The Plant Genome

Genomics and Phylogenetic StudiesChromosomal and Genetic Variations

Cited by 10

Fishing for a reelGene: evaluating gene models with evolution and machine learning

Schulz, A. J., Zhai, J., AuBuchon-Elder, T., El-Walid, M., Ferebee, T. H., Gilmore, E. H., Hufford, M. B., Johnson, L. C., Kellogg, E. A., La, T., et al. (2023) · The Plant Journal

Genomics and Phylogenetic StudiesChromosomal and Genetic Variations

Cited by 9

Fishing for a reelGene : evaluating gene models with evolution and machine learning

Schulz, A. J., Zhai, J., AuBuchon‐Elder, T., Andorf, C. M., El‐Walid, M. Z., Ferebee, T. H., Gilmore, E. H., Hufford, M. B., Johnson, L. C., Kellogg, E. A., et al. (2025) · The Plant Journal

Genomics and Phylogenetic StudiesChromosomal and Genetic Variations

Cited by 9