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

Finding borders between coding and noncoding DNA regions by an entropic segmentation method.

P Bernaola-Galván1, I Grosse, P Carpena

  • 1Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.

Physical Review Letters
|September 16, 2000
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

Evidence for the Collective Nature of Radial Flow in Pb+Pb Collisions with the ATLAS Detector.

Physical review letters·2026
Same author

Evidence for the Dimuon Decay of the Higgs Boson in pp Collisions with the ATLAS Detector.

Physical review letters·2025
Same author

Evidence for Longitudinally Polarized W Bosons in the Electroweak Production of Same-Sign W Boson Pairs in Association with Two Jets in pp Collisions at sqrt[s]=13  TeV with the ATLAS Detector.

Physical review letters·2025
Same author

Observation of tt[over ¯] Production in Pb+Pb Collisions at sqrt[s_{NN}]=5.02  TeV with the ATLAS Detector.

Physical review letters·2025
Same author

Search for Dark Matter Produced in Association with a Dark Higgs Boson in the bb[over ¯] Final State Using pp Collisions at sqrt[s]=13  TeV with the ATLAS Detector.

Physical review letters·2025
Same author

Search for Magnetic Monopole Pair Production in Ultraperipheral Pb+Pb Collisions at sqrt[s_{NN}]=5.36  TeV with the ATLAS Detector at the LHC.

Physical review letters·2025
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

We developed a novel computational method using a 12-letter DNA alphabet and entropic segmentation to accurately identify coding and noncoding DNA borders. This approach surpasses existing methods without needing prior data training.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Distinguishing coding DNA from noncoding DNA is crucial for understanding gene function and regulation.
  • Existing computational methods often rely on extensive training datasets or specific sequence motifs.

Purpose of the Study:

  • To introduce a new computational approach for accurately identifying boundaries between coding and noncoding DNA regions.
  • To develop a method that does not require prior training on known datasets.

Main Methods:

  • Utilizing a 12-letter DNA alphabet to represent base composition at each codon position.
  • Employing an entropic segmentation method based on general statistical properties of coding DNA.

Main Results:

Related Experiment Videos

  • The proposed method accurately identifies borders between coding and noncoding DNA.
  • The approach demonstrates higher accuracy compared to traditional moving window techniques.
  • The method requires no prior training data, enhancing its general applicability.

Conclusions:

  • The novel 12-letter alphabet and entropic segmentation provide a robust and accurate computational tool for DNA border detection.
  • This method offers a significant advancement in distinguishing coding from noncoding DNA sequences.
  • The approach's independence from training data makes it a versatile tool for genomic analysis.