Jove
Visualize
Contact Us

Related Concept Videos

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
FISH - Fluorescent In-situ Hybridization02:07

FISH - Fluorescent In-situ Hybridization

Fluorescence in situ hybridization, or FISH, was developed in the early 1980s and has quickly become one of the most widely used techniques in cytogenetics. Labeled probes are used to bind complementary DNA or RNA sequences on a chromosome or in a region within a cell. Earlier, the probes could only be obtained by cloning or reverse transcription of a DNA template. Currently, the probe oligonucleotides can be synthesized synthetically. Additionally, with the advancement of optical techniques,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Integrated framework for pediatric height assessment: X-ray-based height extreme cases classification and machine learning for multivariate height prediction.

Scientific reports·2026
Same author

A Novel Relative Distance Protein Fingerprint Algorithm for Searching DNA Mimic Proteins.

IEEE transactions on computational biology and bioinformatics·2026
Same author

Subitem-level multi-scale assessment and machine learning for three-class cognitive status classification in Parkinson's disease.

NPJ Parkinson's disease·2025
Same author

P253 Next-generation phenotyping facilitates the identification of structural brain malformations in rare disorders through computational brain MRI analysis.

Genetics in medicine open·2025
Same author

Deep learning-based prediction of mortality using brain midline shift and clinical information.

Heliyon·2025
Same author

Using machine learning to predict bacteremia in urgent care patients on the basis of triage data and laboratory results.

The American journal of emergency medicine·2024
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 Video

Updated: Jun 8, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

An improved heuristic algorithm for finding motif signals in DNA sequences.

Chao-Wen Huang1, Wun-Shiun Lee, Sun-Yuan Hsieh

  • 1Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, University Road, Tainan 70101, Taiwan. huangcw@csie.ncku.edu.tw

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|September 22, 2010
PubMed
Summary

This study introduces a new heuristic algorithm for DNA functional site discovery, improving upon existing motif finding methods. The algorithm effectively identifies planted (l, d)-signals in DNA sequences, showing superior performance on both simulated and real biological data.

More Related Videos

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
12:24

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

Published on: July 21, 2014

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Related Experiment Videos

Last Updated: Jun 8, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
12:24

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

Published on: July 21, 2014

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA functional site discovery is crucial for understanding gene regulation.
  • The planted (l, d)-motif search problem is a key computational challenge in this field.
  • Existing motif finding algorithms have limitations in accuracy and efficiency.

Purpose of the Study:

  • To propose a novel heuristic algorithm for identifying planted (l, d)-signals in DNA sequences.
  • To evaluate the performance of the proposed algorithm against current methods.
  • To demonstrate the algorithm's applicability to real biological data.

Main Methods:

  • Development of a heuristic algorithm tailored for the planted (l, d)-motif search problem.
  • Extensive evaluations using simulated DNA sequence datasets.
  • Experimental validation on real biological datasets.

Main Results:

  • The proposed heuristic algorithm demonstrates superior performance compared to widely used motif finding algorithms.
  • Successful identification of planted (l, d)-signals in simulated datasets.
  • Positive results obtained from experiments on real biological data.

Conclusions:

  • The developed heuristic algorithm is an effective tool for DNA functional site discovery.
  • The algorithm offers an improvement over existing methods for motif finding.
  • The findings support the utility of the algorithm in both theoretical and practical biological applications.