Jove
Visualize
Contact Us
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 Videos

An iterative method for faster sum-of-pairs multiple sequence alignment.

K Reinert1, J Stoye, T Will

  • 1Celera Genomics, Informatics Research, 45 West Gude Drive, Rockville, MD 20850, USA.

Bioinformatics (Oxford, England)
|December 8, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

CT-guided screw fixation of vertical sacral fractures in local anaesthesia using a standard CT.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin·2014
Same author

The Outermost Stratum Corneum Layer is an Effective Barrier Against Dermal Uptake of Topically Applied Micronized Titanium Dioxide.

International journal of cosmetic science·2008
Same author

Correction: Benchmarking tools for the alignment of functional noncoding DNA.

BMC bioinformatics·2004
Same author

QAlign: quality-based multiple alignments with dynamic phylogenetic analysis.

Bioinformatics (Oxford, England)·2003
Same author

Distribution of sunscreens on skin.

Advanced drug delivery reviews·2002
Same author

Common intervals and sorting by reversals: a marriage of necessity.

Bioinformatics (Oxford, England)·2002
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

This study introduces a faster algorithm for multiple sequence alignment using divide-and-conquer and search space reduction. The adaptive method provides optimal or near-optimal alignments efficiently, aiding computational biology research.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Algorithm Development

Background:

  • Multiple sequence alignment is crucial in computational biology.
  • Heuristics are commonly used for speed but may sacrifice accuracy.
  • Optimal multiple alignments are vital for evaluating heuristics and as subprocedures.

Purpose of the Study:

  • To develop a computationally efficient algorithm for multiple sequence alignment.
  • To improve the speed of computing optimal multiple alignments.
  • To provide an adaptive method for obtaining high-quality alignments within time constraints.

Main Methods:

  • Employs a divide-and-conquer strategy for sequence alignment.
  • Integrates recent advancements in search space reduction techniques.

Related Experiment Videos

  • Utilizes the alpha-(*) algorithm for accelerated computation of optimal alignments.

    • Main Results:

    • Presents a novel, adaptive algorithm for multiple sequence alignment.
    • Demonstrates provably improved efficiency over previous exact algorithms.
    • Provides empirical results on the algorithm's effectiveness and limitations.

    Conclusions:

    • The developed algorithm significantly speeds up multiple sequence alignment computation.
    • The adaptive nature allows for flexible alignment quality based on time.
    • This approach enhances the feasibility of obtaining optimal or near-optimal alignments.