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

Classification of genetic sequences with backpropagation

R Lende1, L P Csernai, D Kamp

  • 1Department of Physics, University of Bergen, Norway.

International Journal of Neural Systems
|September 1, 1994
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

Association between effectiveness of treatment with curative intent and outcomes of first-line systemic therapy in metachronous metastatic gastroesophageal adenocarcinoma.

British journal of cancer·2026
Same author

Indication of p + <sup>11</sup>B reaction in Laser Induced Nanofusion experiment.

Scientific reports·2024
Same author

Monitoring of nanoplasmonics-assisted deuterium production in a polymer seeded with resonant Au nanorods using in situ femtosecond laser induced breakdown spectroscopy.

Scientific reports·2024
Same author

Reversible Hypothermia in a Drug-naive Inpatient with Alzheimer's Disease Receiving Pipamperone.

Pharmacopsychiatry·2016
Same author

Inhibition and stimulation of phospholipid scrambling activity. Consequences for lipid asymmetry, echinocytosis, and microvesiculation of erythrocytes.

Biochemistry·2001
Same author

Acceleration of phospholipid flip-flop in the erythrocyte membrane by detergents differing in polar head group and alkyl chain length.

Biochimica et biophysica acta·2000
Same journal

Latent Space Projections and Atlases, a Cautionary Tale in Deep Neuroimaging using Autoencoders.

International journal of neural systems·2026
Same journal

Transformer-Based Anomaly Detection for Neurodegenerative Screening in MRI Images.

International journal of neural systems·2026
Same journal

Discrete Wavelet Convolution for Learnable Time-Frequency Representation with Application to Seizure Prediction.

International journal of neural systems·2026
Same journal

Automatic Seizure Detection using Hierarchical Spectral-Temporal Feature Learning with an Imbalance-Aware Transformer.

International journal of neural systems·2026
Same journal

Pyramid Vision Transformer-Enhanced Conformer Network for Epileptic Seizure Recognition Using MultiChannel EEG Signals.

International journal of neural systems·2026
Same journal

A Time-Frequency Decoupled Contrastive Learning Framework for Electroencephalography-Based Parkinson's Disease Diagnosis.

International journal of neural systems·2026
See all related articles

This study uses a neural network trained with a backpropagation algorithm to classify prokaryotic and eukaryotic species based on DNA doublet frequencies, achieving a 15% improvement over single-doublet statistical analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Distinguishing between prokaryotic and eukaryotic species is fundamental in biology.
  • Traditional statistical methods for species classification can be limited in accuracy.

Purpose of the Study:

  • To develop and evaluate a neural network model for classifying prokaryotic and eukaryotic species.
  • To assess the effectiveness of using DNA doublet frequencies for classification.

Main Methods:

  • A backpropagation algorithm was employed to train a neural network.
  • The network was trained using frequencies of all 16 DNA doublets from known species.
  • The model's performance was tested on unseen DNA sequences.

Main Results:

Related Experiment Videos

  • The neural network achieved an approximate 15% improvement in classification accuracy compared to methods using only one doublet.
  • The model demonstrated effective discrimination between prokaryotic and eukaryotic DNA sequences.

Conclusions:

  • Neural networks trained on DNA doublet frequencies offer a more accurate method for species classification.
  • This approach enhances the ability to differentiate between major biological domains.