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

Inferring regulatory networks.

Huai Li1, Jianhua Xuan, Yue Wang

  • 1Bioinformatics Unit, Branch of Research Resources, National Institute on Aging, NIH, Baltimore, MD, USA. huaili@mail.nih.gov <huaili@mail.nih.gov>

Frontiers in Bioscience : a Journal and Virtual Library
|November 6, 2007
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

MAE-UNETR++: Masked Autoencoder Pretraining for 3-D Lung Nodule Segmentation.

bioRxiv : the preprint server for biology·2026
Same author

MRI radiomics and <sup>90</sup>Y PET dosimetry for predicting hepatocellular carcinoma response after radioembolization.

BMC cancer·2026
Same author

Urinary bisphenol A analogues and metabolically unhealthy obesity in school-age children.

Environmental pollution (Barking, Essex : 1987)·2026
Same author

First large-scale screening of Notch biallelic variants implicates novel candidate genes in congenital hypothyroidism.

The Journal of clinical endocrinology and metabolism·2026
Same author

Removal of pentavalent vanadium from water by Fe-Ni loaded multi-walled carbon nanotubes.

Journal of environmental management·2026
Same author

Editorial: Microbial ecological and biogeochemical processes in the soil-vadose zone-groundwater habitats, volume III.

Frontiers in microbiology·2026
Same journal

The CD44 protein family: roles in embryogenesis and tumor progression.

Frontiers in bioscience : a journal and virtual library·2017
Same journal

Four varieties of voltage-gated proton channels.

Frontiers in bioscience : a journal and virtual library·2017
Same journal

Lurie's tubercle-count method to test TB vaccine efficacy in rabbits.

Frontiers in bioscience : a journal and virtual library·2017
Same journal

Optical spectroscopy of breast biopsies and human breast cancer xenografts in nude mice.

Frontiers in bioscience : a journal and virtual library·2017
Same journal

The colostrum-deprived, artificially-reared, neonatal pig as a model animal for studying rotavirus gastroenteritis.

Frontiers in bioscience : a journal and virtual library·2017
Same journal

Action of polypeptide growth factors in colon cancer; development of new therapeutic approaches.

Frontiers in bioscience : a journal and virtual library·2017
See all related articles

Discovering gene regulatory networks is crucial in post-genomic research, requiring systems biology approaches. This review covers computational methods for inferring these networks using gene expression data.

Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Post-genomic research increasingly relies on understanding complex gene regulatory networks.
  • Identifying these networks is essential for deciphering cellular functions and disease mechanisms.
  • Integrated experimental and computational strategies are vital for network discovery.

Purpose of the Study:

  • To review major computational themes in the inference of gene regulatory networks.
  • To discuss methods for transcriptional module identification, network topology inference, and network analysis.
  • To evaluate the merits of popular computational solutions for network inference.

Main Methods:

  • Computational inference of regulatory networks.
  • Analysis of gene expression data.

Related Experiment Videos

  • Systems biology approaches.

    • Main Results:

    • Summary of key computational strategies for regulatory network discovery.
    • Discussion of methods for identifying transcriptional modules.
    • Evaluation of techniques for network topology inference and analysis.

    Conclusions:

    • Computational inference is a powerful tool for understanding gene regulatory networks.
    • The review highlights various methods and their comparative advantages.
    • Systems biology approaches are central to advancing regulatory network research.