An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq data.
Transcription factors are proteins that bind to specific DNA sequences and play important roles in controlling the expression levels of their target genes. Hence, prediction of transcription factor binding sites (TFBSs) provides a solid foundation for inferring gene regulatory mechanisms and building regulatory networks for a genome. Chromatin immunoprecipitation sequencing (ChIP-seq) technology can generate large-scale experimental data for such protein-DNA interactions, providing an unprecedented opportunity to identify TFBSs (a.k.a. cis-regulatory motifs). The bottleneck, however, is the lack of robust mathematical models, as well as efficient computational methods for TFBS prediction to make effective use of massive ChIP-seq data sets in the public domain. The purpose of this study is to review existing motif-finding methods for ChIP-seq data from an algorithmic perspective and provide new computational insight into this field. The state-of-the-art methods were shown through summarizing eight representative motif-finding algorithms along with corresponding challenges, and introducing some important relative functions according to specific biological demands, including discriminative motif finding and cofactor motifs analysis. Finally, potential directions and plans for ChIP-seq-based motif-finding tools were showcased in support of future algorithm development.
School of Mathematics, Shandong University, Jinan Shandong, P. R. China.
Bingqiang
B
Liu
Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA.
Jinyu
J
Yang
School of Mathematics, Shandong University, Jinan Shandong, P. R. China.
Yang
Y
Li
Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA.
Adam
A
McDermaid
Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD, USA.
Qin
Q
Ma
D000465:Algorithms; D001483:Base Sequence; D001665:Binding Sites / Q000235:genetics; D047369:Chromatin Immunoprecipitation / Q000706:statistics & numerical data; D019295:Computational Biology / Q000379:methods; D004247:DNA / Q000235:genetics / Q000378:metabolism; D053263:Gene Regulatory Networks; D006801:Humans; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data; D012984:Software; D014157:Transcription Factors / Q000378:metabolism
D014157:Transcription Factors; D004247:DNA