Chapter title |
Predicting Functional MicroRNA-mRNA Interactions
|
---|---|
Chapter number | 10 |
Book title |
MicroRNA Detection and Target Identification
|
Published in |
Methods in molecular biology, April 2017
|
DOI | 10.1007/978-1-4939-6866-4_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6864-0, 978-1-4939-6866-4
|
Authors |
Zixing Wang, Yin Liu |
Editors |
Tamas Dalmay |
Abstract |
MicroRNAs (miRNAs) are small RNA molecules that play key regulatory roles in general biological processes and disease pathogenesis. These small RNA molecules interact with their target mRNAs to induce mRNA degradation and/or inhibit the translation of mRNAs into proteins. Therefore, identifying miRNA targets is an essential step to fully understand the regulatory effects of miRNAs. Here, we describe a regularized regression approach that integrates the sequence information with the miRNA and mRNA expression profiles for detecting miRNA targets. This method takes into account the full spectrum of gene sequence features of miRNA targets, including the thermodynamic stability, the accessibility energy, and the context features of the target sites,. Given these sequence features for each putative miRNA-mRNA interaction and their expression values, this model is able to quantify the down-regulation effect of each miRNA on its targets while simultaneously estimating the contribution of each sequence feature for predicting functional miRNA-mRNA interactions. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 10 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 4 | 40% |
Professor | 3 | 30% |
Student > Master | 1 | 10% |
Unknown | 2 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 40% |
Environmental Science | 1 | 10% |
Agricultural and Biological Sciences | 1 | 10% |
Chemistry | 1 | 10% |
Unknown | 3 | 30% |