蛋白质的亚细胞定位的预测
描写人多的四字词语
关于蛋白质的网络英文怎么写亚细胞定位的预测,In general高钓马,预测方法分为3个步骤。首先,为每一类亚细胞locations构建客观而具有代表性的数据集。其次,从数据集中提取特征参数或 descriptor。最后也是最关键的一步,通过算法比较查询序列中所包含的特征参数与各类相应的location的相似度,作出判断,一般会用一组概率的形式来表述。很明显,其中大量运用的是机器学习理论和统计学的方法。对算法有兴趣的朋友可以参考下面这一篇综述,“An overview on predicting the subcellular location of a protein” In Silico Biology 2002 www.bioinfo.de/isb/2002/02/0027/main.html
以下是该综述中涉及的部分rver,都是比较经典的。
PSORT:psort.nibb.ac.jp
By amino acid composition information and sorting signal knowledge
TargetP黑米补血吗:www.cbs.dtu.dk/rvices/TargetP/
By discriminating the individual targeting signal peptide
MitoProt:ihg.gsf.de/ihg/mitoprot.html
By discriminating mitochondrial and chloroplast signal peptide
Predotar:www.inra.fr/Internet/Produits/Predotar/
By discriminating mitochondrial, chloroplast signal peptide
NNPSL:predict.sanger.ac.uk/nnpsl
By amino acid composition 团队目标口号
SobLoc:www.bioinfo./SubLoc/
推销与营销的区别By amino acid composition
SubLoc: www.bioinfo./SubLoc/
By more quence information besides the amino acid composition
一篇文献:lumbia.edu/papers/2003_loci_3dnet/paper.html
外商独资企业法“Better prediction of sub-cellular localization by combining evolutionary and structural information”
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