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

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for

E P Xing1, D M Wolf, I Dubchak

  • 1Center for Bioinformatics and Computational Genomics, NERSC, Berkeley, CA 94720, USA.

Journal of Theoretical Biology
|September 5, 2001
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

Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival.

Annals of oncology : official journal of the European Society for Medical Oncology·2020
Same author

Trimethylamine-N-oxide is elevated in the acute phase after ischaemic stroke and decreases within the first days.

European journal of neurology·2020
Same author

["Hand, foot, eye?"]

Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft·2019
Same author

Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types.

Nature communications·2019
Same author

A new family of transcriptional regulators of tungstoenzymes and molybdate/tungstate transport.

Environmental microbiology·2018
Same author

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with polynomial functions.

Heredity·2017
Same journal

The male-biased sex ratio in humans and its role in the transition from promiscuity to pair bonding.

Journal of theoretical biology·2026
Same journal

Quantifying the counter-intuitive effects of vaccination by coupling the transmission dynamics of COVID-19 and the evolution of human behaviors.

Journal of theoretical biology·2026
Same journal

An integrative model of FGF2-induced signaling and muscle cell proliferation.

Journal of theoretical biology·2026
Same journal

A hybrid reaction-diffusion and mechanical stimulus model for mandibular bone remodeling under chewing and vibratory loading.

Journal of theoretical biology·2026
Same journal

Integrated tick management strategies in fragmented peridomestic environments.

Journal of theoretical biology·2026
Same journal

Joint likelihood-free inference of the number of selected single nucleotide polymorphisms and their selection coefficients in an evolving population.

Journal of theoretical biology·2026
See all related articles

This study introduces a novel segmentation algorithm for automatically identifying biologically significant segments within multi-aligned sequences. The method efficiently detects conserved domains, variable motifs, and rare signatures in molecular data.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Evolution

Background:

  • Accurate identification of sub-structures in multi-aligned sequences is crucial for molecular analyses.
  • Current methods for domain annotation and phylogenetic analysis can be subjective or inefficient.
  • Automating the detection of biologically significant segments is a key challenge.

Purpose of the Study:

  • To develop and present an algorithm for the optimal segmentation of multi-aligned sequences.
  • To automatically identify biologically significant blocks or segments within large sequence datasets.
  • To facilitate objective structural, functional, and evolutionary annotation of molecular sequences.

Main Methods:

  • The algorithm employs dynamic programming and progressive optimization techniques.

Related Experiment Videos

  • It analyzes the statistical profile of multi-alignments to demarcate homogenous sub-regions.
  • The method was applied to a large multi-alignment of eukaryotic 16S ribosomal RNA (rRNA) sequences.

    • Main Results:

    • The algorithm successfully and efficiently identified three distinct sequence patterns: shared conserved domains, shared variable motifs, and rare signature sequences.
    • These automatically identified patterns were consistent with findings from independent phylogenetic and structural analyses.
    • The segmentation approach demonstrated high performance computation for large datasets.

    Conclusions:

    • The developed segmentation algorithm provides an effective and objective method for analyzing multi-aligned sequences.
    • It automates key aspects of molecular structural and evolutionary analyses.
    • This approach holds significant potential for advancing bioinformatics and computational biology research.