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

1. BMC Genomics reviewer acknowledgement 2015

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   Authors: Derek Anane

   Citation: BMC Genomics 2016 17:168

   Content type: Reviewer acknowledgement Published on: 2 March 2016

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2. The interplay of demography and selection during maize domestication and expansion

   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

   Content type: Research Published on: 13 November 2017

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3. Medical Subject Heading (MeSH) annotations illuminate maize genetics and evolution

   High-density marker panels and/or whole-genome sequencing, coupled with advanced phenotyping pipelines and sophisticated statistical methods, have dramatically increased our ability to generate lists of candid...

   Authors: Timothy M. Beissinger and Gota Morota

   Citation: Plant Methods 2017 13:8

   Content type: Methodology Published on: 23 February 2017

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4. Annual acknowledgement of reviewers

   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

   Content type: Reviewer acknowledgement Published on: 29 February 2016

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5. Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

   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

   Content type: Research Published on: 25 September 2012

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6. Defining window-boundaries for genomic analyses using smoothing spline techniques

   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

   Content type: Research Published on: 17 April 2015

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7. Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs

   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

   Content type: Research article Published on: 8 October 2019

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