Titlebook: RNA Bioinformatics; Ernesto Picardi Book 2015 Springer Science+Business Media New York 2015 DNA.Non-coding RNAs.RNA bioinformatics.RNA dat

緩解

Quantifying Entire Transcriptomes by Aligned RNA-Seq Datanalysis are very complex and the choice of different tools at each stage of the analysis can significantly affect the overall results. In this chapter we describe the pipelines we use to detect miRNA and mRNA differential expression.

單調(diào)性

Lyme-disease

Expressly

MAOIS

De Novo Secondary Structure Motif Discovery Using RNAProfilery elements present functional motifs, conserved both in structure and sequence, that can be hardly detected by primary sequence analysis alone. We describe here how conserved secondary structure motifs shared by functionally related RNA sequences can be detected through the software tool RNAProfile

單純

Drawing and Editing the Secondary Structure(s) of RNAisually as drafts or finalized publication-ready figures. While many tools are currently available to automate the production of such diagrams, their capacities are usually partial, making it hard for a user to decide which to use in a given context. In this chapter, we guide the reader through the

暖昧關(guān)系

Migratory

Fast Prediction of RNA–RNA Interaction Using Heuristic Algorithms, an RNA molecule prohibits the translation of another RNA molecule by establishing stable interactions with it. Some algorithms have been formed to predict the structure of the RNA–RNA interaction. High computational time is a common challenge in most of the presented algorithms. In this context,

Countermand

deciduous