A survey on algorithms to characterize transcription factor binding sites

被引:8
|
作者
Tognon, Manuel
Giugno, Rosalba [1 ,5 ]
Pinello, Luca [2 ,3 ,4 ,6 ,7 ]
机构
[1] Univ Verona, Comp Sci Dept, Verona, Italy
[2] Massachusetts Gen Hosp, Mol Pathol Unit, Ctr Canc Res, Charlestown, MA 02129 USA
[3] Harvard Med Sch, Dept Pathol, Boston, MA 02115 USA
[4] Broad Inst Harvard & MIT, Cambridge, MA 02142 USA
[5] Univ Verona, Verona, Italy
[6] Massachusetts Gen Hosp, Charlestown, MA USA
[7] Harvard Med Sch, Boston, MA USA
基金
欧盟地平线“2020”;
关键词
transcription factors; transcription factors motif discovery; motif discovery algorithms; motif models; PROTEIN-DNA INTERACTIONS; GENOME-WIDE ANALYSIS; CHIP-SEQ; MOTIF DISCOVERY; REGULATORY ELEMENTS; SIMPLE-MODELS; EM ALGORITHM; SEQUENCE; CHROMATIN; DEEP;
D O I
10.1093/bib/bbad156
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Transcription factors (TFs) are key regulatory proteins that control the transcriptional rate of cells by binding short DNA sequences called transcription factor binding sites (TFBS) or motifs. Identifying and characterizing TFBS is fundamental to understanding the regulatory mechanisms governing the transcriptional state of cells. During the last decades, several experimental methods have been developed to recover DNA sequences containing TFBS. In parallel, computational methods have been proposed to discover and identify TFBS motifs based on these DNA sequences. This is one of the most widely investigated problems in bioinformatics and is referred to as the motif discovery problem. In this manuscript, we review classical and novel experimental and computational methods developed to discover and characterize TFBS motifs in DNA sequences, highlighting their advantages and drawbacks. We also discuss open challenges and future perspectives that could fill the remaining gaps in the field.
引用
收藏
页数:16
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