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

Sequence alignment kernel for recognition of promoter regions.

Leo Gordon1, Alexey Ya Chervonenkis, Alex J Gammerman

  • 1Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk

Bioinformatics (Oxford, England)
|October 14, 2003
PubMed
Summary

This study introduces a novel Sequence Alignment Kernel and Dual SVM method for identifying prokaryotic promoter regions. The new approach demonstrates strong performance in recognizing transcription startpoints in E. coli.

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

Validation and Clinical Meaningfulness of the 18-item National Comprehensive Cancer Network/Functional Assessment of Cancer Therapy Lymphoma Symptom Index in Patients With Lymphoma.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2026
Same author

A phase 1-2 trial of DA-EPOCH-R plus ixazomib for MYC-aberrant lymphoid malignancies: the DACIPHOR regimen.

Blood advances·2024
Same author

Dual targeting fixed duration frontline monoclonal antibody therapy for chronic lymphocytic leukemia: A phase 2 study.

Leukemia research·2022
Same author

Cachexia is a risk factor for negative clinical and functional outcomes in patients receiving chimeric antigen receptor T-cell therapy for B-cell non-Hodgkin lymphoma.

British journal of haematology·2022
Same author

Aggressive morphologic variants of mantle cell lymphoma characterized with high genomic instability showing frequent chromothripsis, CDKN2A/B loss, and TP53 mutations: A multi-institutional study.

Genes, chromosomes & cancer·2020
Same author

Spoof plasmons enable giant Raman scattering enhancement in Near-Infrared region.

Optics express·2019

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate identification of prokaryotic promoter regions is crucial for understanding gene regulation.
  • Existing methods for promoter recognition require improvement in accuracy and efficiency.

Purpose of the Study:

  • To develop and evaluate a new computational method for recognizing prokaryotic promoter regions, including transcription startpoints.
  • To assess the performance of the proposed method using established datasets.

Main Methods:

  • Development of a Sequence Alignment Kernel to quantify sequence similarity.
  • Application of the kernel within a Dual Support Vector Machine (SVM) framework for promoter recognition.
  • Training and testing on a dataset of 669 sigma70-promoter regions from Escherichia coli and negative datasets from coding and non-coding regions.

Related Experiment Videos

Main Results:

  • The proposed method achieved an average error rate of 16.5% on positive and coding negative data.
  • An average error rate of 18.6% was obtained on positive and non-coding negative data.
  • The method demonstrates effective performance in recognizing promoter regions.

Conclusions:

  • The Sequence Alignment Kernel combined with Dual SVM offers a promising approach for prokaryotic promoter recognition.
  • The developed method shows competitive accuracy for identifying transcription startpoints in E. coli.
  • A demo version of the method is available online for further research and application.