Recent advances in statistical methods and genomic technologies have ushered in a new era in mapping clinically important quantitative traits. However, many refinements and novel statistical approaches are required to enable greater successes in this mapping. The possible impact of recent findings pertaining to the structure of the human genome on efforts to map quantitative traits is yet unclear.
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Univ Alabama, Dept Math, Tuscaloosa, AL 35487 USA
Univ Washington, Dept Biostat, Seattle, WA 98195 USAUniv Alabama, Dept Math, Tuscaloosa, AL 35487 USA
Laurie, Cecelia
Wang, Shengchu
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N Carolina State Univ, Dept Stat, Bioinformat Res Ctr, Raleigh, NC 27695 USAUniv Alabama, Dept Math, Tuscaloosa, AL 35487 USA
Wang, Shengchu
Carlini-Garcia, Luciana Aparecida
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Inst Agron Campinas, Ctr Graos & Fibras, Campinas, SP, Brazil
APTA Reg, Polo Ctr Sul, Piracicaba, SP, BrazilUniv Alabama, Dept Math, Tuscaloosa, AL 35487 USA
Carlini-Garcia, Luciana Aparecida
Zeng, Zhao-Bang
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N Carolina State Univ, Dept Stat, Bioinformat Res Ctr, Raleigh, NC 27695 USA
N Carolina State Univ, Dept Biol Sci, Raleigh, NC 27695 USAUniv Alabama, Dept Math, Tuscaloosa, AL 35487 USA
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Limagrain Verneuil Holding, Département Recherche, Zone Indust. de la MétairieLimagrain Verneuil Holding, Département Recherche, Zone Indust. de la Métairie
Parisseaux B.
Bernardo R.
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Dept. of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, St. Paul, MN 55108Limagrain Verneuil Holding, Département Recherche, Zone Indust. de la Métairie