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

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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  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