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

Sequencing-by-hybridization at the information-theory bound: an optimal algorithm.

F P Preparata1, E Upfal

  • 1Computer Science Department, Brown University, Providence, RI 02912-1910, USA. franco@cs.brown.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|December 7, 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

Optimal reconstruction of a sequence from its probes.

Journal of computational biology : a journal of computational molecular cell biology·1999
Same author

Ciliate evolution: the ribosomal phylogenies of the tetrahymenine ciliates.

Journal of molecular evolution·1989
Same author

Shifting ditypic site analysis: heuristics for expanding the phylogenetic range of nucleotide sequences in Sankoff analyses.

Journal of molecular evolution·1989
Same journal

Mosquito Species and Gender Identification System Based on Artificial Intelligence and Image Processing Methods.

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

A new DNA sequencing algorithm enhances the gapped-probe scheme for DNA sequencing by hybridization (SBH). This method offers high-confidence performance close to theoretical limits with linear running time.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • The standard oligomer probe scheme for DNA sequencing by hybridization (SBH) has limitations in sequence reconstruction.
  • A novel gapped-probe scheme combining natural and universal bases was previously introduced, showing improved performance over standard methods.

Purpose of the Study:

  • To present and analyze a new, more powerful sequencing algorithm specifically designed for the gapped-probe SBH scheme.
  • To demonstrate that the new algorithm achieves near information-theory bound performance for SBH.

Main Methods:

  • Development and theoretical analysis of a novel sequencing algorithm for the gapped-probe SBH scheme.
  • Mathematical proof demonstrating the algorithm's efficiency and performance bounds.

Related Experiment Videos

Main Results:

  • The new algorithm significantly enhances the capabilities of the gapped-probe SBH scheme.
  • The algorithm achieves high-confidence performance within a small constant factor (approximately 2) of the information-theory bound.
  • The algorithm maintains a running time linear in the target sequence length.

Conclusions:

  • The developed algorithm represents a substantial advancement in SBH technology.
  • This algorithm maximizes the potential of the gapped-probe scheme, offering efficient and accurate DNA sequencing.
  • The findings pave the way for more effective DNA sequencing by hybridization applications.