Complementary classification approaches for protein sequences.
Complementary classification approaches for protein sequences.
复制标题
蛋白质序列的补充分类方法。
DOI：
10.1093/protein/9.5.381
复制
发表时间：
1996
期刊：
影响因子：
--
通讯作者：
Lee,TY
中科院分区：
文献类型：
--
作者：
Wang,JT;Marr,TG;Shasha,D;Shapiro,BA;Chirn,GW;Lee,TY
我们研究了五种蛋白质分类方法，并将其应用于PROSITE目录中的768组相关蛋白质。其中四种方法是基于搜索数据库的块，和其他使用的蛋白质家族中发现的频繁出现的图案结合指纹技术。我们的实验结果表明，基于块的方法表现良好时，考虑到出现在一个块中的氨基酸的概率。此外，这五种方法提供的信息是相辅相成的。因此，同时使用这五种方法，可以获得高置信度的分类（如果结果一致）或提出替代假设（如果结果不一致）。我们还列出了那些蛋白质，其目前的家庭记录在PROSITE目录不同于我们的结果所建议的。他们中的一些人非常少，这证明了PROSITE的质量。
We have studied five methods of protein classification and have applied them to the 768 groups of related proteins in the PROSITE catalog. Four of these methods are based on searching a database of blocks, and the other uses the frequently occurring motifs found in the protein families combined with a fingerprint technique. Our experimental results show that the block-based methods perform well when taking into account the probability of amino acids occurring in a block. Furthermore, the five methods give information that is complementary to each other. Thus, using the five methods together, one can obtain high confidence classifications (if the results agree) or suggest alternative hypotheses (if the results disagree). We also list those proteins whose current families documented in the PROSITE catalog differ from those suggested by our results. There are remarkably few of them, which is a testimony to the quality of PROSITE.