Computational Prediction of RNA-Protein Interactions.

PROMOTER ASSOCIATED RNA: METHODS AND PROTOCOLS(2017)

引用 10|浏览22
暂无评分
摘要
Experimental methods for identifying protein(s) bound by a specific promoter-associated RNA (paRNA) of interest can be expensive, difficult, and time-consuming. This chapter describes a general computational framework for identifying potential binding partners in RNA-protein complexes or RNA-protein interaction networks. Protocols for using three web-based tools to predict RNA-protein interaction partners are outlined. Also, tables listing additional webservers and software tools for predicting RNA-protein interactions, as well as databases that contain valuable information about known RNA-protein complexes and recognition sites for RNA-binding proteins, are provided. Although only one of the tools described, lncPro, was designed expressly to identify proteins that bind long noncoding RNAs (including paRNAs), all three approaches can be applied to predict potential binding partners for both coding and noncoding RNAs (ncRNAs).
更多
查看译文
关键词
RNA-protein interactions, Computational prediction, RPISeq, catRAPID, lncPRO, RNA-protein databases, Machine learning, ncRNA
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要