Literature DB >> 17993680

Discovering sequence motifs.

Timothy L Bailey1.   

Abstract

Sequence motif discovery algorithms are an important part of the computational biologist's toolkit. The purpose of motif discovery is to discover patterns in biopolymer (nucleotide or protein) sequences to better understand the structure and function of the molecules the sequences represent. This chapter provides an overview of the use of sequence motif discovery in biology and a general guide to the use of motif discovery algorithms. This chapter examines the types of biological features that DNA and protein motifs can represent and their usefulness. This chapter also defines what sequence motifs are, how they are represented, and general techniques for discovering them. The primary focus of the chapter is on one aspect of motif discovery: discovering motifs in a set of unaligned DNA or protein sequences. This chapter also provides the steps useful for checking the biological validity and investigating the function of sequence motifs using methods such as motif scanning-searching for matches to motifs in a given sequence or a database of sequences. A discussion of some limitations of motif discovery concludes the chapter.

Mesh:

Substances:

Year:  2007        PMID: 17993680     DOI: 10.1007/978-1-59745-514-5_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Parametric bootstrapping for biological sequence motifs.

Authors:  Patrick K O'Neill; Ivan Erill
Journal:  BMC Bioinformatics       Date:  2016-10-06       Impact factor: 3.169

2.  MEME SUITE: tools for motif discovery and searching.

Authors:  Timothy L Bailey; Mikael Boden; Fabian A Buske; Martin Frith; Charles E Grant; Luca Clementi; Jingyuan Ren; Wilfred W Li; William S Noble
Journal:  Nucleic Acids Res       Date:  2009-05-20       Impact factor: 16.971

3.  Quad-PRE: a hybrid method to predict protein quaternary structure attributes.

Authors:  Yajun Sheng; Xingye Qiu; Chen Zhang; Jun Xu; Yanping Zhang; Wei Zheng; Ke Chen
Journal:  Comput Math Methods Med       Date:  2014-05-18       Impact factor: 2.238

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.