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

Local decoding of sequences and alignment-free comparison.

Gilles Didier1, Ivan Laprevotte, Maude Pupin

  • 1Institut de Mathématiques de Luminy, UMR 6206, Campus de Luminay, Case 907, 13288 Marseille, France. didier@iml.univ-mrs.fr

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 26, 2006
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

Testing extinction events and temporal shifts in diversification and fossilization rates through the skyline Fossilized Birth-Death (FBD) model: The example of some mid-Permian synapsid extinctions.

Cladistics : the international journal of the Willi Hennig Society·2024
Same author

The Cauchy Process on Phylogenies: A Tractable Model for Pulsed Evolution.

Systematic biology·2023
Same author

Norine: Bioinformatics Methods and Tools for the Characterization of Newly Discovered Nonribosomal Peptides.

Methods in molecular biology (Clifton, N.J.)·2023
Same author

Editorial: Timetrees: Incorporating fossils and molecules.

Frontiers in genetics·2022
Same author

Turbo prediction: a new approach for bioactivity prediction.

Journal of computer-aided molecular design·2022
Same author

Distributions of extinction times from fossil ages and tree topologies: the example of mid-Permian synapsid extinctions.

PeerJ·2021
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

We introduce local decoding of order N, a novel method for sequence analysis that captures environmental information efficiently. This approach offers a computationally efficient alternative to subword methods for sequence comparison.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Subword composition is crucial for sequence analysis.
  • Existing subword methods have limitations in capturing sequence environments.
  • There is a need for efficient and informative sequence analysis techniques.

Purpose of the Study:

  • To define and study "local decoding of order N of sequences" as an alternative to subword methods.
  • To develop an efficient algorithm for computing local decoding.
  • To demonstrate the utility of local decoding in sequence comparison.

Main Methods:

  • Developed an algorithm for computing local decoding of order N for sequence sets.
  • The algorithm's time and memory complexity are linear with respect to sequence length, independent of order N.

Related Experiment Videos

  • Proposed a dissimilarity measure based on local decoding and evaluated its accuracy.

    • Main Results:

    • The proposed algorithm for local decoding is computationally efficient (linear time and space).
    • Local decoding provides a basis for sequence dissimilarity measures.
    • The accuracy of local decoding-based dissimilarity was evaluated against alignment-based distances and other alignment-free methods.

    Conclusions:

    • Local decoding of order N is an effective method for sequence analysis, preserving environmental information.
    • The developed algorithm offers significant computational advantages.
    • Local decoding shows promise as a component of alignment-free sequence comparison methods.