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用于识别增强子-靶基因对的计算生物学解决方案

Computational Biology Solutions to Identify Enhancers-target Gene Pairs.

作者信息

Hariprakash Judith Mary, Ferrari Francesco

机构信息

IFOM, The FIRC Institute of Molecular Oncology, Milan, Italy.

Institute of Molecular Genetics, National Research Council, Pavia, Italy.

出版信息

Comput Struct Biotechnol J. 2019 Jun 14;17:821-831. doi: 10.1016/j.csbj.2019.06.012. eCollection 2019.

Abstract

Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality.

摘要

增强子是与其靶基因距离较远的非编码调控元件。由于在实现增强子与靶基因的全面配对方面存在挑战,其特征仍难以捉摸。利用功能基因组学数据的日益可得性以及对增强子作用机制理解的改进,已经提出了许多计算生物学解决方案来解决这个问题。在本综述中,我们重点关注全基因组增强子 - 靶基因对定义的计算方法。我们概述了不同类别的方法及其主要优点和局限性。介绍并讨论了每种方法整合的信息类型及其适用性细节。我们特别强调了仍未解决且阻碍有效实现令人满意和全面解决方案的技术挑战。我们预计,由于数据的不断增加以及对增强子在调节基因组功能中关键作用的深入了解,该领域在未来几年将持续发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8131/6611831/2e8b65f410ad/gr1.jpg

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