Computational Non coding RNA Biology is popular PDF and ePub book, written by Yun Zheng in 2018-09-14, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Computational Non coding RNA Biology can be Read Online from any device for your convenience.

Computational Non coding RNA Biology Book PDF Summary

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

Detail Book of Computational Non coding RNA Biology PDF

Computational Non coding RNA Biology
  • Author : Yun Zheng
  • Release : 14 September 2018
  • Publisher : Academic Press
  • ISBN : 9780128143667
  • Genre : Science
  • Total Page : 320 pages
  • Language : English
  • PDF File Size : 11,8 Mb

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