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 optimal algorithm for perfect phylogeny haplotyping.

Ravi Vijayasatya1, Amar Mukherjee

  • 1School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, 32816-2362, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|June 10, 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

The undirected incomplete perfect phylogeny problem.

IEEE/ACM transactions on computational biology and bioinformatics·2008
Same author

Constructing near-perfect phylogenies with multiple homoplasy events.

Bioinformatics (Oxford, England)·2006
Same author

A pattern matching algorithm for codon optimization and CpG motif-engineering in DNA expression vectors.

Proceedings. IEEE Computer Society Bioinformatics Conference·2006
Same author

An efficient algorithm for Perfect Phylogeny Haplotyping.

Proceedings. IEEE Computational Systems Bioinformatics Conference·2006
Same author

DNA sequence compression using the burrows-wheeler transform.

Proceedings. IEEE Computer Society Bioinformatics Conference·2005
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

This study introduces an efficient O(nm) algorithm for the perfect phylogeny haplotyping problem, significantly improving upon previous O(nm^2) methods. The new approach utilizes a FlexTree data structure for faster haplotype inference, crucial for disease-gene association studies.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genetics

Background:

  • Haplotype inference from genotype data is vital for identifying genetic variants associated with human diseases.
  • The perfect phylogeny haplotyping (PPH) problem is a key computational approach to haplotype inference.
  • Previous PPH algorithms had a time complexity of O(nm^2), hindering large-scale applications.

Purpose of the Study:

  • To develop a more efficient algorithm for the perfect phylogeny haplotyping problem.
  • To reduce the computational complexity of haplotype inference.
  • To facilitate the linkage of single nucleotide polymorphisms (SNPs) to human diseases.

Main Methods:

  • Leveraging column-ordering to identify interdependencies between SNP sites.

Related Experiment Videos

  • Introducing the FlexTree data structure for compact representation of pairwise relationships (O(m) space).
  • Developing a sequential genotype addition method and an O(nm) algorithm (OPPH).

    • Main Results:

    • The proposed OPPH algorithm achieves a time complexity of O(nm).
    • The FlexTree data structure efficiently represents all possible perfect phylogenies.
    • Simulated data demonstrated the OPPH algorithm's impressive performance compared to existing methods.

    Conclusions:

    • The O(nm) OPPH algorithm offers a significant advancement in haplotype inference efficiency.
    • This improved computational approach can accelerate the discovery of disease-related genetic markers.
    • The FlexTree data structure provides a novel and compact representation for perfect phylogenies.