Bioinformatics Tools for Genome-Wide Epigenetic Research

被引:39
作者
Angarica, Vladimir Espinosa [1 ]
del Sol, Antonio [1 ]
机构
[1] Univ Luxembourg, Luxembourg Ctr Syst Biomed, Computat Biol Grp, 6 Ave Swing, L-4366 Belvaux, Luxembourg
来源
NEUROEPIGENOMICS IN AGING AND DISEASE | 2017年 / 978卷
关键词
Computational epigenetics; Histone code; Epigenetics regulation; Transcriptional regulation; Next generation sequencing analysis; Single cell neuroepigenetics; CHIP-SEQ DATA; SINGLE-CELL TRANSCRIPTOMICS; TANDEM MASS-SPECTROMETRY; DNA METHYLATION DATA; ELECTRON-CAPTURE DISSOCIATION; GRAPHICAL USER-INTERFACE; GENE NETWORK INFERENCE; EMBRYONIC STEM-CELLS; SHORT READ ALIGNMENT; FACTOR-BINDING SITES;
D O I
10.1007/978-3-319-53889-1_25
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Epigenetics play a central role in the regulation of many important cellular processes, and dysregulations at the epigenetic level could be the source of serious pathologies, such as neurological disorders affecting brain development, neurodegeneration, and intellectual disability. Despite significant technological advances for epigenetic profiling, there is still a need for a systematic understanding of how epigenetics shapes cellular circuitry, and disease pathogenesis. The development of accurate computational approaches for analyzing complex epigenetic profiles is essential for disentangling the mechanisms underlying cellular development, and the intricate interaction networks determining and sensing chromatin modifications and DNA methylation to control gene expression. In this chapter, we review the recent advances in the field of "computational epigenetics," including computational methods for processing different types of epigenetic data, prediction of chromatin states, and study of protein dynamics. We also discuss how "computational epigenetics" has complemented the fast growth in the generation of epigenetic data for uncovering the main differences and similarities at the epigenetic level between individuals and the mechanisms underlying disease onset and progression.
引用
收藏
页码:489 / 512
页数:24
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