| Author(s) | Yun Zheng |
 | Year | 2019
|
 | Pages | 299 |
 | Language | English |
 | Format | PDF |
 | Size | 30.5 MB
|
 | Publisher | Academic Press |
 | ISBN | 0128143657, 978-0128143650, B07HF4NP5G |
Computational Non-coding RNA Biology
is a resource for the computation of non-coding RNAs. The book covers
computational methods for the identification and quantification of
non-coding RNAs, including miRNAs, tasiRNAs, phasiRNAs, lariat
originated circRNAs and back-spliced circRNAs, the identification of
miRNA/siRNA targets, and the identification of mutations and editing
sites in miRNAs. The book introduces basic ideas of computational
methods, along with their detailed computational steps, a critical
component in the development of high throughput sequencing technologies
for identifying different classes of non-coding RNAs and predicting the
possible functions of these molecules.
Finding, quantifying, and
visualizing non-coding RNAs from high throughput sequencing datasets at
high volume is complex. Therefore, it is usually possible for
biologists to complete all of the necessary steps for analysis.
- Presents a comprehensive resource of computational methods for the identification and quantification of non-coding RNAs
- Introduces 23 practical computational pipelines for various topics of non-coding RNAs
- Provides a guide to assist biologists and other researchers dealing with complex datasets
- Introduces basic computational methods and provides guidelines for their replication by researchers
- Offers a solution to researchers approaching large and complex sequencing datasets
