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 mi RNAs, tasi RNAs, phasi RNAs, lariat originated circ RNAs and back-spliced circ RNAs, the identification of mi RNA/si RNA targets, and the identification of mutations and editing sites in mi RNAs. The book introduces basic ideas of computational methods, along with their detailed c...
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 mi RNAs, tasi RNAs, phasi RNAs, lariat originated circ RNAs and back-spliced circ RNAs, the identification of mi RNA/si RNA targets, and the identification of mutations and editing sites in mi RNAs. 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
