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Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: May 24, 2026

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

CPU-GPU hybrid accelerating the Zuker algorithm for RNA secondary structure prediction applications.

Guoqing Lei1, Yong Dou, Wen Wan

  • 1National Laboratory for Parallel & Distributed Processing, Department of Computer Science, National University of Defense Technology, Changsha 410073, China. guoqinglei2007@gmail.com

BMC Genomics
|February 29, 2012
PubMed
Summary

This study introduces a hybrid CPU-GPU system to accelerate RNA secondary structure prediction using the Zuker algorithm. The novel approach significantly speeds up computations, outperforming optimized single-processor methods.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA secondary structure prediction is crucial in bioinformatics.
  • The Zuker algorithm is a key method for predicting RNA secondary structures.
  • Accelerating the Zuker algorithm on hardware accelerators like GPUs is an active research area.

Purpose of the Study:

  • To propose a novel CPU-GPU hybrid computing system for accelerating RNA secondary structure prediction.
  • To optimize the Zuker algorithm for parallel execution on both CPU and GPU architectures.
  • To achieve workload balance between CPU and GPU for enhanced performance.

Main Methods:

  • Development of a CPU-GPU hybrid system for parallel execution of the Zuker algorithm.
  • Task allocation between CPU and GPU considering performance differences for workload balancing.
  • Optimized implementation of the Zuker algorithm tailored for CPU and GPU architectures.

Main Results:

  • Achieved a speedup of 15.93× compared to an optimized multi-core SIMD CPU implementation.
  • Demonstrated a 16% performance advantage over an optimized GPU-only implementation.
  • Successfully executed over 14% of sequences on the CPU within the hybrid system.

Conclusions:

  • The proposed CPU-GPU hybrid system offers a promising approach to accelerate Zuker algorithm applications.
  • This hybrid system demonstrates significant performance gains for RNA secondary structure prediction.
  • The hybrid computing strategy is adaptable for accelerating other bioinformatics applications.