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

Improving signal peptide prediction accuracy by simulated neural network.

I Ladunga1, F Czakó, I Csabai

  • 1Department of Genetics, Eötvös University, Budapest, Hungary.

Computer Applications in the Biosciences : CABIOS
|October 1, 1991
PubMed
Summary

This study enhances signal peptide prediction accuracy to 95% by integrating a neural network with statistical methods. This improved technique identified 496 novel signal peptides, advancing protein research.

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

Fourier transform mid-infrared imaging and rapid evaporative ionization mass spectrometry imaging in FFPE colorectal adenocarcinoma samples.

Pathologie (Heidelberg, Germany)·2025
Same author

Corrigendum to: Breast cancer brain metastases show increased levels of genomic aberration-based homologous recombination deficiency scores relative to their corresponding primary tumors.

Annals of oncology : official journal of the European Society for Medical Oncology·2019
Same author

Breast cancer brain metastases show increased levels of genomic aberration-based homologous recombination deficiency scores relative to their corresponding primary tumors.

Annals of oncology : official journal of the European Society for Medical Oncology·2018
Same author

Loss of BRCA1 or BRCA2 markedly increases the rate of base substitution mutagenesis and has distinct effects on genomic deletions.

Oncogene·2017
Same author

Fast and accurate mutation detection in whole genome sequences of multiple isogenic samples with IsoMut.

BMC bioinformatics·2017
Same author

Loss of BRCA1 or BRCA2 markedly increases the rate of base substitution mutagenesis and has distinct effects on genomic deletions.

Oncogene·2016

Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Proteomics

Background:

  • Accurate identification of signal peptides is crucial for understanding protein localization and function.
  • Existing prediction methods, like von Heijne's statistical approach, have limitations in accuracy.

Purpose of the Study:

  • To improve the accuracy of distinguishing signal peptides from cytosolic proteins.
  • To identify novel signal peptides using an enhanced prediction methodology.

Main Methods:

  • A neural network classifier was combined with von Heijne's statistical prediction method.
  • The neural network processed amino-terminal 20-residue segments using a 'tiling' algorithm, focusing on segments rather than cleavage sites.
  • Concordant predictions from both methods were used for identification.

Related Experiment Videos

Main Results:

  • The combined approach achieved a prediction accuracy of 95%.
  • This method successfully identified 496 novel signal peptides from the Protein Identification Resources database.
  • The reliability of von Heijne's method alone is 85-90%.

Conclusions:

  • The integration of neural networks and statistical prediction significantly enhances signal peptide identification accuracy.
  • This refined method provides a reliable tool for discovering new signal peptides, contributing to proteomic and cell biology research.