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

Recognition of gene acceptor site based on multi-objective optimization.

Jing Zhao1, Yue-Min Zhu, Pei-Ming Song

  • 1School of Life Science and Technology, Shanghai Jiaotong University, Shanghai 200240, China.

Acta Biochimica Et Biophysica Sinica
|July 7, 2005
PubMed
Summary

This study introduces a novel multi-objective optimization method for predicting gene acceptor sites. The new approach demonstrates superior performance compared to existing splice site detection tools.

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

IFDlong: a model-based isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data.

Genome biology·2026
Same author

Deep spatial sequencing revealing differential immune responses in human hepatocellular carcinoma.

Frontiers in cell and developmental biology·2025
Same author

Comparative analysis of plane vs. telescopic dissection in totally extraperitoneal inguinal hernia repair: propensity score matching.

Surgical endoscopy·2025
Same author

Deep Spatial Sequencing Revealing Differential Immune Responses in Human Hepatocellular Carcinoma.

bioRxiv : the preprint server for biology·2025
Same author

Comparing simple and functional jejunal interposition with preserved duodenal passage after total gastrectomy.

Asian journal of surgery·2024
Same author

Utility analyses of AVITI sequencing chemistry.

BMC genomics·2024

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate prediction of gene acceptor sites is crucial for understanding gene structure and function.
  • Existing methods for splice site detection have limitations in accuracy and efficiency.
  • The exon-intron database provides valuable sequence characteristics for model development.

Purpose of the Study:

  • To develop a novel computational method for predicting gene acceptor sites.
  • To improve the accuracy of splice site recognition using multi-objective optimization.
  • To compare the performance of the new method against established splice site detectors.

Main Methods:

  • Construction of predictive models for acceptor sites, branch sites, and their distances.
  • Definition of acceptor, branch, and distance functions based on sequence characteristics.

Related Experiment Videos

  • Development of a multi-objective optimization model for splice site recognition.

    • Main Results:

    • The developed multi-objective optimization model effectively recognizes splice sites.
    • The proposed algorithm shows improved performance over the SplicePredictor.
    • The method leverages biological knowledge and sequence characteristics from exon-intron databases.

    Conclusions:

    • The novel multi-objective optimization method offers a promising approach for gene acceptor site prediction.
    • This method enhances the accuracy of splice site detection in bioinformatics.
    • Further development could integrate this method into broader genomic analysis pipelines.