Accuracy-driven loci selection and assignment of individuals

被引：21
|
作者：
Topchy, A [1 ]
Scribner, K
Punch, W
机构：
[1] Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA
[3] Michigan State Univ, Dept Zool, E Lansing, MI 48824 USA
来源：
MOLECULAR ECOLOGY NOTES | 2004年 / 4卷 / 04期
关键词：
genetic algorithm; individual classification; locus selection; maximum likelihood;
D O I：
10.1111/j.1471-8286.2004.00781.x
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
We present two programs: GAFS for optimal selection of loci for use in individual assignment tests, and MLC, a program for individual classification using maximum likelihood and k-nearest neighbour decision rules. GAFS software employs a genetic algorithm to heuristically search multilocus subsets with several objective functions to maximize predictive accuracy of the assignments. Keywords: genetic algorithm, individual classification, locus selection, maximum likelihood.
引用
收藏
页码：798 / 800
页数：3
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