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10 result(s) for 'author#Timothy M. Beissinger' within BMC

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  1. The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay be...

    Authors: Li Wang, Timothy M. Beissinger, Anne Lorant, Claudia Ross-Ibarra, Jeffrey Ross-Ibarra and Matthew B. Hufford
    Citation: Genome Biology 2017 18:215
  2. The editors of BMC Evolutionary Biology would like to thank all our reviewers who have contributed to the journal in Volume 15 (2015).

    Authors: Christopher Foote
    Citation: BMC Evolutionary Biology 2016 16:54
  3. This report provides information about the public release of the 2018–2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and...

    Authors: Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Bridget A. McFarland, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Candice N. Hirsch, Elizabeth Hood…
    Citation: BMC Genomic Data 2023 24:29
  4. The Genomes to Fields (G2F) 2022 Maize Genotype by Environment (GxE) Prediction Competition aimed to develop models for predicting grain yield for the 2022 Maize GxE project field trials, leveraging the datase...

    Authors: Dayane Cristina Lima, Jacob D. Washburn, José Ignacio Varela, Qiuyue Chen, Joseph L. Gage, Maria Cinta Romay, James Holland, David Ertl, Marco Lopez-Cruz, Fernando M. Aguate, Gustavo de los Campos, Shawn Kaeppler, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards…
    Citation: BMC Research Notes 2023 16:148
  5. This release note describes the Maize GxE project datasets within the Genomes to Fields (G2F) Initiative. The Maize GxE project aims to understand genotype by environment (GxE) interactions and use the informa...

    Authors: Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Alden Perkins, Dylan L Schoemaker, Martin Costa, Kathryn J. Michel, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards…
    Citation: BMC Research Notes 2023 16:219
  6. Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selec...

    Authors: Xiao-Lin Wu, Chuanyu Sun, Timothy M Beissinger, Guilherme JM Rosa, Kent A Weigel, Natalia de Leon Gatti and Daniel Gianola
    Citation: Genetics Selection Evolution 2012 44:29
  7. High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, s...

    Authors: Timothy M Beissinger, Guilherme JM Rosa, Shawn M Kaeppler, Daniel Gianola and Natalia de Leon
    Citation: Genetics Selection Evolution 2015 47:30
  8. Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop...

    Authors: Abiskar Gyawali, Vivek Shrestha, Katherine E. Guill, Sherry Flint-Garcia and Timothy M. Beissinger
    Citation: BMC Plant Biology 2019 19:412