下一代测序技术数据中的选择性剪切计算识别方法研究

Computational Identification of Alternative Splicing in Next-Generation Sequencing Data

随着测序技术的发展,下一代测序技术(Nex-t Generation Sequencing)给生物信息学领域研究带来了新的机遇和挑战.由于选择性剪切(alternative splicing,AS)在真核生物基因表达和蛋白质多样性方面的重要性,识别选择性剪切位点一直都是研究的重点.下一代测序技术的出现,使得选择性剪切研究的计算方法不断地变化.介绍了选择性剪切过去和目前研究的状况,然后总结了基于RNA-seq数据的选择性剪切研究方法、软件以及数据库,并利用了RNA-seq数据比较了相关软件,最后讨论了选择性剪切中计算方法的发展方向和前景.

With the development of sequencing technology, Next-Generation Sequencing brought opportunities and challenges to the bioinformatics. As the importance of alternative splicing in gene expression and protein diversity in eukaryotes, alternative splicing identification has been the focus of bioinformatics research. The computation methods for alternative splicing need to be im- proved since the appearance of Next-Generation Sequencing. We introduce the past and current research of AS firstly; then conclude and compare the research methods, software and databases of AS based on RNA-seq data; finally try to discuss the development and prospect of the computational methods on AS.