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

Non-parametric classification of protein secondary structures.

Elias Zintzaras1, Nigel P Brown, Axel Kowald

  • 1Department of Biomathematics, University of Thessaly School of Medicine, Greece. zintza@med.uth.gr

Computers in Biology and Medicine
|January 4, 2006
PubMed
Summary

A novel classification tree method effectively groups proteins into families based on secondary structure properties. This approach outperforms other methods like neural networks and support vector machines for protein classification.

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

Inferring accumulation times of mitochondrial DNA deletion mutants from cross-sectional single-cell data: methodological framework and validation.

npj aging·2026
Same author

Glucagon-like Peptide-1 Receptor Agonists and Platelet Function: Potential Benefits Beyond Glycemic Control.

Pharmaceuticals (Basel, Switzerland)·2026
Same author

Assessment of the Reporting Quality of Randomized, Controlled Trials of Percutaneous Patent Foramen Ovale Closure for the Treatment of Migraine Based on the CONSORT Statement.

Innovations in clinical neuroscience·2025
Same author

Multicohort study testing the generalisability of the SASKit-ML stroke and PDAC prognostic model pipeline to other chronic diseases.

BMJ open·2024
Same author

A Risk-Difference Meta-Analysis for the Prophylactic Treatments of Chronic Migraine.

Cureus·2024
Same author

Healthy Aging in Times of Extreme Temperatures: Biomedical Approaches.

Aging and disease·2023

Area of Science:

  • * Bioinformatics and computational biology.
  • * Protein structure analysis and classification.

Background:

  • * Accurate protein family classification is crucial for understanding protein function and evolution.
  • * Existing methods for protein classification have limitations in speed and accuracy.

Purpose of the Study:

  • * To introduce and evaluate a new classification tree method for protein family classification.
  • * To compare the performance of the classification tree method against dynamic programming, neural networks, and support vector machines.

Main Methods:

  • * Proteins classified using a classification tree method based on physico-chemical and geometrical properties of secondary structures.
  • * Tree splitting criterion: increase in purity; tree size controlled by apparent misclassification rate (AMR) threshold.

Related Experiment Videos

  • * Comparison with dynamic programming, neural networks, and support vector machines.

    • Main Results:

    • * The classification tree method demonstrated effectiveness in reproducing structural groupings similar to dynamic programming.
    • * The proposed method showed superior performance in classifying proteins into their families compared to neural networks and support vector machines.
    • * The algorithm achieved a better classification accuracy.

    Conclusions:

    • * The developed classification tree method is a robust and accurate tool for protein family classification.
    • * This algorithm offers a potentially rapid preliminary classification of proteins.
    • * The method provides a valuable alternative for large-scale protein family analysis.