DocumentCode :
864692
Title :
Image Analysis for Mapping Immeasurable Phenotypes in Maize [Life Sciences]
Author :
Shyu, Chi-Ren ; Green, Jason M. ; Lun, Daniel P K ; Kazic, Toni ; Schaeffer, Mary ; Coe, Ed
Author_Institution :
Missouri-Columbia Univ., Columbia, MO
Volume :
24
Issue :
3
fYear :
2007
fDate :
5/1/2007 12:00:00 AM
Firstpage :
115
Lastpage :
118
Abstract :
This work will allow bio-informaticians to analyze the ever-increasing gene sequence data, discover valuable knowledge in maize biology and related plant; development, and understand subtle variations among different phenotypes. Furthermore, successful measuring of visual phenotypes will advance plant research by finding the genes and/or environmental factors that cause a given visual phenotype. In what follows, the field of plant genetics is introduced (particularly quantitative trait loci and disease scoring) to the signal processing community, discuss the challenges involved, and present an image analysis system for precisely quantifying and mapping immeasurable phenotypes in maize
Keywords :
biology computing; crops; genetics; image sequences; gene sequence data; image analysis; maize biology; mapping immeasurable phenotypes; plant genetics; signal processing; visual phenotype; Bioinformatics; Couplings; Crops; Diseases; Environmental factors; Genetics; Genomics; Image analysis; Image sequence analysis; Ontologies;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2007.361609
Filename :
4205096
Link To Document :
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