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Related Concept Videos

RNA Structure01:19

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...
RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
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...
Nucleic Acid Structure01:25

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA has a double-helix structure. The...

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Related Experiment Video

Updated: Jun 25, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Fine-grained parallel RNAalifold algorithm for RNA secondary structure prediction on FPGA.

Fei Xia1, Yong Dou, Xingming Zhou

  • 1National Laboratory for Parallel&Distributed Processing, Department of Computer Science, National University of Defense Technology, ChangSha, 410073, PR China. xcyphoenix@nudt.edu.cn

BMC Bioinformatics
|February 12, 2009
PubMed
Summary

Field Programmable Gate-Array (FPGA) chips accelerate RNA secondary structure prediction using the RNAalifold algorithm. This novel FPGA implementation achieves a 12.2x speedup, overcoming limitations of traditional computing platforms.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Hardware Acceleration

Background:

  • RNA secondary structure prediction is crucial in molecular biology.
  • The RNAalifold algorithm is a popular method for this task, but suffers from limited parallel efficiency on conventional hardware.
  • Field Programmable Gate-Array (FPGA) chips offer potential for fine-grained custom hardware acceleration.

Purpose of the Study:

  • To develop an FPGA-based accelerator for the RNAalifold algorithm.
  • To overcome the parallel efficiency limitations of general-purpose computers for RNA structure prediction.

Main Methods:

  • Designed a systolic array architecture with master and slave Processing Elements (PEs) for FPGA implementation.
  • Exploited data reuse schemes to minimize external memory access for energy matrices.
  • Developed methods to reduce the energy table parameter size by 80%.

Main Results:

  • Implemented a complete RNAalifold algorithm on an FPGA with 16 PEs.
  • Achieved a 12.2-fold speedup compared to the software version (ViennaPackage - 1.6.5) on a PC.
  • Demonstrated significant acceleration for long RNA sequences (2981 residues).

Conclusions:

  • This work presents the first known FPGA accelerator for the complete RNAalifold algorithm.
  • FPGA acceleration offers a substantial performance improvement for RNA secondary structure prediction.
  • The proposed architecture and optimization techniques are effective for hardware implementation of complex bioinformatics algorithms.