Gathering Computational Genomics and Proteomics to Unravel Adaptive Evolution

被引:0
|
作者
Antunes, Agostinho [1 ]
Ramos, Maria Joao [1 ]
机构
[1] Univ Porto, Fac Ciencias, Dept Quim, REQUIMTE, P-4169007 Oporto, Portugal
来源
EVOLUTIONARY BIOINFORMATICS | 2007年 / 3卷
关键词
bioinformatics; positive selection; molecular adaptation;
D O I
暂无
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A recent editorial in PLoS Biology by MacCallum and Hill (2006) pointed out the inappropriateness of studies evaluating signatures of positive selection based solely in single-site analyses. Therefore the rising number of articles claiming positive selection that have been recently published urges the question of how to improve the bioinformatics standards for reliably unravel positive selection? Deeper integrative efforts using state-of-the-art methodologies at the gene-level and protein-level are improving positive selection studies. Here we provide some computational guidelines to thoroughly document molecular adaptation.
引用
收藏
页码:207 / 209
页数:3
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