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 Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Cell Signaling in Plants01:25

Cell Signaling in Plants

Plant cells communicate to coordinate their cycle of growth, flowering and fruiting, and activities in roots, shoots, and leaves in response to the changing environmental conditions. Plant signaling is distinct from animal signaling. Plants primarily utilize enzyme-linked receptors, whereas the largest class of cell-surface receptors in animals are G-protein coupled receptors (GPCRs). Unlike animals, receptor tyrosine kinases are rare in plants. Instead, plants have a diverse class of...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

You might also read

Related Articles

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

Sort by
Same author

Seeds in suspension: Cell type-specific control of seed dormancy and germination initiation.

Current opinion in plant biology·2026
Same author

Molecular mechanisms of transhydrogenase activity and allosteric regulation in eukaryotic type II PHGDH Ser33.

Nature communications·2026
Same author

ZFHX4 is necessary for dopaminergic neuron differentiation and controls cell cycle by regulating LIN28A.

Stem cell reports·2026
Same author

SARS-CoV-2 Infection Induces Dopaminergic Neuronal Loss in Midbrain Organoids.

Journal of neurochemistry·2026
Same author

Therapeutic subtypes of knee osteoarthritis: differential treatment effects among predicted endotypes in past clinical trials.

Arthritis research & therapy·2026
Same author

Generation of Brassica napus with enhanced Sclerotinia sclerotiorum resistance through CRISPR/Cas9-mediated inhibition of the PROTEOLYSIS6 N-degron pathway.

The New phytologist·2026
Same journal

The Plant RABC1 GTPase Coordinates with Exocyst Component SEC5A in Regulating ER-phagy under Endoplasmic Reticulum Stress.

The Plant cell·2026
Same journal

Graft transmissible resistance to Alternaria alternata is mediated by rootstock to scion JA transport activating raffinose synthesis.

The Plant cell·2026
Same journal

What fresh cell is this? Building a single-cell atlas of developing grass leaves in Brachypodium distachyon.

The Plant cell·2026
Same journal

The STA1-DOT2 interaction promotes nuclear speckle formation and splicing robustness in growth and heat stress responses.

The Plant cell·2026
Same journal

GIGANTEA shapes diurnal seedling growth by sequestering SMAX1 and SMXL2.

The Plant cell·2026
Same journal

Vascular-specific genome editing enhances low-phosphate tolerance in rice.

The Plant cell·2026
See all related articles

Related Experiment Video

Updated: May 29, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

George W Bassel1, Enrico Glaab, Julietta Marquez

  • 1Division of Plant and Crop Sciences, University of Nottingham, Loughborough, Leicestershire, UK. george.bassel@nottingham.ac.uk

The Plant Cell
|September 8, 2011
PubMed
Summary
This summary is machine-generated.

We developed a new machine learning method, coprediction, to find gene functions from large datasets. This approach identified novel regulators of Arabidopsis seed germination, creating a valuable community resource.

More Related Videos

High-throughput, Robust and Highly Time-flexible Method for Surface Sterilization of Arabidopsis Seeds
07:28

High-throughput, Robust and Highly Time-flexible Method for Surface Sterilization of Arabidopsis Seeds

Published on: October 4, 2021

A Simple Protocol for Mapping the Plant Root System Architecture Traits
11:09

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Published on: February 10, 2023

Related Experiment Videos

Last Updated: May 29, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

High-throughput, Robust and Highly Time-flexible Method for Surface Sterilization of Arabidopsis Seeds
07:28

High-throughput, Robust and Highly Time-flexible Method for Surface Sterilization of Arabidopsis Seeds

Published on: October 4, 2021

A Simple Protocol for Mapping the Plant Root System Architecture Traits
11:09

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Published on: February 10, 2023

Area of Science:

  • Computational Biology
  • Genomics
  • Machine Learning

Background:

  • Large-scale genomic data analysis offers novel biological insights.
  • Gene coexpression analysis is used to understand gene function.
  • Existing methods may miss functional relationships due to expression similarity.

Purpose of the Study:

  • To present a novel computational method, coprediction, for identifying functional gene relationships using rule-based machine learning.
  • To apply coprediction to Arabidopsis thaliana seed microarray data to create a functional gene interaction network (SCoPNet).
  • To identify novel regulators of seed germination and their interactions.

Main Methods:

  • Utilized rule-based machine learning for gene functional relationship identification.
  • Applied the coprediction approach to public Arabidopsis thaliana microarray data.
  • Constructed the Seed Co-Prediction Network (SCoPNet) to predict gene interactions.

Main Results:

  • Coprediction accurately predicts developmental outcomes based on co-occurring gene groups.
  • SCoPNet identified functional associations between genes in the same pathways, regardless of expression similarity.
  • Discovered four novel regulators of Arabidopsis seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8).
  • Predicted transcript abundance interactions between novel and known seed germination factors.

Conclusions:

  • Coprediction is a powerful tool for uncovering gene function and interactions from genomic data.
  • SCoPNet provides a valuable resource for seed biology research.
  • The identified novel regulators and predicted interactions advance understanding of Arabidopsis seed germination.