title: AMD, an automated motif discovery tool using stepwise refinement of gapped consensuses.
abstract: Motif discovery is essential for deciphering regulatory codes from high throughput genomic data, such as those from ChIP-chip/seq experiments. However, there remains a lack of effective and efficient methods for the identification of long and gapped motifs in many relevant tools reported to date. We describe here an automated tool that allows for de novo discovery of transcription factor binding sites, regardless of whether the motifs are long or short, gapped or contiguous.
authors.affiliation: Key Laboratory of Stem Cell Biology, Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Jiantao
authors.initials: J
authors.lastname: Shi
authors.forename: Wentao
authors.initials: W
authors.lastname: Yang
authors.forename: Mingjie
authors.initials: M
authors.lastname: Chen
authors.forename: Yanzhi
authors.initials: Y
authors.lastname: Du
authors.forename: Ji
authors.initials: J
authors.lastname: Zhang
authors.forename: Kankan
authors.initials: K
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs / Q000235:genetics*; D000818:Animals; D001331:Automation; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000737:chemistry; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors; D004247:DNA