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

Model identification for DNA sequence-structure relationships.

Stephen Dwyer Hawley1, Anita Chiu, Howard Jay Chizeck

  • 1Cogent Systems Research Laboratory, Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA.

Mathematical Biosciences
|April 11, 2006
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

Cortical Brain-Computer Interface for Closed-Loop Deep Brain Stimulation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2017
Same author

Empirical Movement Models for Brain Computer Interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2016
Same author

Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson's Disease.

Movement disorders : official journal of the Movement Disorder Society·2016
Same author

A proxy method for real-time 3-DOF haptic rendering of streaming point cloud data.

IEEE transactions on haptics·2014
Same author

Creating the feedback loop: closed-loop neurostimulation.

Neurosurgery clinics of North America·2013
Same author

Inferior hemorrhoidal artery pseudoaneurysm presenting as gastrointestinal bleed.

The American surgeon·2011
Same journal

The hydra and hormetic effects in a single discrete-time overcompensation model.

Mathematical biosciences·2026
Same journal

Seasonal impacts on brucellosis transmission mediated by live sheep supply-demand dynamics.

Mathematical biosciences·2026
Same journal

Optimal controls and cost-effectiveness analysis on the transmission dynamics of early blight disease in tomatoes.

Mathematical biosciences·2026
Same journal

Temperature-dependent dynamics and allee effect thresholds mediate fourfold cusp stability in biological control of invasive vectors.

Mathematical biosciences·2026
Same journal

Dynamics of a stochastic tumor-immune interaction system with an Ornstein-Uhlenbeck process.

Mathematical biosciences·2026
Same journal

Post-peak dynamics and epidemic overshoot in SIR-type frameworks.

Mathematical biosciences·2026
See all related articles

Algebraic state-space models efficiently predict DNA sequence-dependent properties like Slide. These models, treating DNA as an input signal, offer accurate structural predictions with reduced computational cost compared to physical models.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Predicting DNA sequence-dependent properties is crucial for understanding genomic function.
  • Traditional all-atom physical models are computationally intensive.
  • Developing efficient models for DNA structural properties remains a challenge.

Purpose of the Study:

  • To investigate algebraic state-space models for sequence-dependent DNA properties.
  • To develop efficient methods for model structure determination and parameter estimation.
  • To assess the accuracy and computational efficiency of these models for DNA structure prediction.

Main Methods:

  • Representing DNA sequence as an input signal for algebraic state-space models.
  • Developing two candidate model structures for the DNA structural property 'Slide'.

Related Experiment Videos

  • Employing a recursive least squares algorithm for parameter estimation after model encoding.

    • Main Results:

    • Two models for predicting DNA 'Slide' based on tetranucleotide sequences were developed.
    • Model 1 (individual bases) achieved a median root mean square deviation (RMSD) of 0.90 Å.
    • Model 2 (pairwise bases) achieved a median RMSD of 0.88 Å, demonstrating high accuracy.

    Conclusions:

    • Algebraic state-space models provide accurate predictions of DNA sequence-dependent structural properties.
    • These models offer significant computational efficiency compared to physical models.
    • The developed models are suitable for DNA structure prediction applications.