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

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

Dong Li1, Zhisong Pan2, Guyu Hu2

  • 1School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK.

BMC Genomics
|April 1, 2017
PubMed
Summary

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

Tenacibaculum xiamenense sp. nov., an algicidal bacterium isolated from coastal seawater.

International journal of systematic and evolutionary microbiology·2013
Same author

The anchoring protein SAP97 influences the trafficking and localisation of multiple membrane channels.

Biochimica et biophysica acta·2013
Same author

Aegilops tauschii draft genome sequence reveals a gene repertoire for wheat adaptation.

Nature·2013
Same author

Draft genome of the wheat A-genome progenitor Triticum urartu.

Nature·2013
Same author

Citreoviridin enhances tumor necrosis factor-α-induced adhesion of human umbilical vein endothelial cells.

Toxicology and industrial health·2013
Same author

Th17/Treg imbalance induced by increased incidence of atherosclerosis in patients with systemic lupus erythematosus (SLE).

Clinical rheumatology·2013
Same journal

Chromosomal scale genome assembly of medicinal plant Sophora tonkinensis.

BMC genomics·2026
Same journal

Variant-specific RNA testing resolves variants of uncertain significance in exome testing.

BMC genomics·2026
Same journal

Kaiso overexpression promotes an interferon immune response in murine intestines.

BMC genomics·2026
Same journal

Genomic evidence of ecological flexibility and cross-niche CRISPR spacerome targeting phage-plasmid hybrids in Latilactobacillus curvatus.

BMC genomics·2026
Same journal

Fgf evolution in vertebrates: insights from cyclostomes.

BMC genomics·2026
Same journal

Metabolic reprogramming, oxidative stress, and mitophagy in JSRV Env-transformed BEAS-2B cells: insights from integrated transcriptomics and metabolomics.

BMC genomics·2026
See all related articles
This summary is machine-generated.

This study introduces a new algorithm for identifying active modules in biological networks using a memetic algorithm. The method ensures module connectedness and improves performance for analyzing cellular responses.

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Active modules are crucial connected regions in biological networks exhibiting significant expression changes under specific conditions.
  • Identifying these modules aids in uncovering regulatory and signaling pathways linked to cellular responses.

Purpose of the Study:

  • To present a novel algorithm for active module identification.
  • To enhance the accuracy and efficiency of detecting biologically relevant modules in complex networks.

Main Methods:

  • Development of a novel active module identification algorithm.
  • Implementation of a memetic algorithm with a unique encoding/decoding scheme to guarantee module connectedness.
  • Integration of a local search operator to optimize algorithm performance.
Keywords:
ConnectednessMemetic algorithmModule identificationModule size

Related Experiment Videos

Main Results:

  • The proposed algorithm effectively identifies active modules.
  • The novel encoding/decoding scheme ensures the connectedness of identified modules.
  • The local search operator enhances the algorithm's overall performance.

Conclusions:

  • The developed algorithm is effective for active module identification.
  • Validation on both small and large protein interaction networks confirms its robustness and scalability.