Jove
Visualize
Contact Us

Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

GnnDebugger: GNN based error correction in De Bruijn Graphs.

BMC bioinformatics·2026
Same author

A complete human pancreatic cancer genome.

bioRxiv : the preprint server for biology·2026
Same author

Telomere-to-telomere assembly using HERRO-corrected Nanopore Simplex reads.

Nature·2026
Same author

MADRe: Strain-level metagenomic classification through assembly-driven database reduction.

GigaScience·2026
Same author

Campolina: a deep neural framework for accurate segmentation of nanopore signals.

Genome biology·2026
Same author

A complete diploid human genome benchmark for personalized genomics.

bioRxiv : the preprint server for biology·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 9, 2026

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

SW#-GPU-enabled exact alignments on genome scale.

Matija Korpar1, Mile Šikic

  • 1Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR 10000 Zagreb, Croatia and Bioinformatics Institute, A*STAR, #07-01 Matrix, 138671 Singapore.

Bioinformatics (Oxford, England)
|July 19, 2013
PubMed
Summary

We developed SW#, a fast and memory-efficient implementation of the Smith-Waterman algorithm using CUDA graphical processing units (GPUs). SW# is the first publicly available GPU implementation capable of genome-wide local sequence alignment.

More Related Videos

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

Related Experiment Videos

Last Updated: May 9, 2026

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Algorithm Development

Background:

  • The Smith-Waterman algorithm is crucial for local sequence alignment in bioinformatics.
  • Existing GPU implementations of Smith-Waterman lack public availability for genome-wide scale analysis.

Purpose of the Study:

  • To introduce SW#, a novel, memory-efficient, and GPU-enabled implementation of the Smith-Waterman algorithm.
  • To provide a publicly accessible tool for large-scale sequence alignment.

Main Methods:

  • Development of a CUDA-based graphical processing unit (GPU) implementation of the dynamic programming algorithm for local alignment.
  • Optimization for memory efficiency and performance on GPU architectures.

Main Results:

  • SW# achieves significant speedups, being hundreds of times faster than CPU-based implementations for long sequences.
  • SW# is the first publicly available GPU implementation capable of genome-wide scale sequence alignment.

Conclusions:

  • SW# offers a powerful and efficient solution for local sequence alignment, particularly for large-scale genomic data.
  • The software is available as a stand-alone application or a library, enhancing its utility for researchers.