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Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...
Types of RNA01:20

Types of RNA

Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in regulating gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA Performs Diverse...
Types of RNA01:23

Types of RNA

Overview
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in the regulation of gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
Ribosome biogenesis begins with the synthesis of 5S and 45S pre-rRNAs by distinct RNA polymerases. The primary transcripts are extensively processed and modified before they are bound and folded by ribosomal proteins and assembly factors,...

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Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries
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Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Published on: December 1, 2023

Computational analysis of noncoding RNAs.

Stefan Washietl1, Sebastian Will, David A Hendrix

  • 1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. wash@mit.edu

Wiley Interdisciplinary Reviews. RNA
|September 20, 2012
PubMed
Summary
This summary is machine-generated.

This review covers computational methods for analyzing noncoding RNAs (ncRNAs). It details techniques for RNA structure prediction, genomic annotation, novel transcript discovery, and microRNA analysis, aiding biological research.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Noncoding RNAs (ncRNAs) play crucial roles in cellular functions.
  • The diverse functions of ncRNAs present significant challenges for experimental and computational biologists.
  • A comprehensive understanding of ncRNA mechanisms requires advanced analytical approaches.

Purpose of the Study:

  • To review computational methods for analyzing noncoding RNAs.
  • To provide an overview of techniques for RNA structure prediction and annotation.
  • To highlight resources for studying ncRNA functions and roles.

Main Methods:

  • Review of computational techniques for RNA structure prediction (basic and advanced).
  • Methods for annotating noncoding RNAs within genomic datasets.
  • Analysis of RNA-sequencing (RNA-seq) data for novel transcript identification and structure prediction.
  • Computational approaches for microRNA analysis.
  • Overview of relevant database resources.

Main Results:

  • Compilation of essential computational tools and strategies for ncRNA research.
  • Detailed explanation of methods for predicting RNA secondary and tertiary structures.
  • Guidance on identifying and characterizing novel ncRNA transcripts from sequencing data.
  • Summary of computational pipelines for microRNA discovery and target prediction.

Conclusions:

  • Computational methods are indispensable for deciphering the complex roles of noncoding RNAs.
  • This review offers a valuable resource for researchers in experimental and computational biology.
  • Effective utilization of computational tools can accelerate the discovery of novel ncRNA functions and applications.