Bailey Timothy L
University of Queensland, Brisbane, Australia.
Curr Protoc Bioinformatics. 2002 Nov;Chapter 2:Unit 2.4. doi: 10.1002/0471250953.bi0204s00.
This unit illustrates how to use MEME to discover motifs in a group of related nucleotide or peptide sequences. A MEME motif is a sequence pattern that occurs repeatedly in one or more sequences in the input group. MEME can be used to discover novel patterns because it bases its discoveries only on the input sequences, not on any prior knowledge (such as databases of known motifs). The input to MEME is a set of unaligned sequences of the same type (peptide or nucleotide). For each motif it discovers, MEME reports the occurrences (sites), consensus sequence, and the level of conservation (information content) at each position in the pattern. MEME also produces block diagrams showing where all of the discovered motifs occur in the training set sequences. MEME's hypertext (HTML) output also contains buttons that allow for the convenient use of the motifs in other searches.
本单元阐述了如何使用MEME在一组相关的核苷酸或肽序列中发现基序。MEME基序是一种序列模式,它在输入组中的一个或多个序列中反复出现。MEME可用于发现新的模式,因为它的发现仅基于输入序列,而不依赖于任何先验知识(如已知基序的数据库)。MEME的输入是一组相同类型(肽或核苷酸)的未比对序列。对于它发现的每个基序,MEME会报告其出现情况(位点)、共有序列以及模式中每个位置的保守程度(信息含量)。MEME还会生成框图,展示所有发现的基序在训练集序列中的出现位置。MEME的超文本(HTML)输出还包含按钮,方便在其他搜索中使用这些基序。