Computational and Experimental Identification of Tissue-Specific MicroRNA Targets.
Methods Mol Biol
; 1580: 127-147, 2017.
Article
em En
| MEDLINE
| ID: mdl-28439832
ABSTRACT
In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Regulação da Expressão Gênica
/
Genômica
/
MicroRNAs
Tipo de estudo:
Diagnostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article