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

Improving Translational Accuracy02:07

Improving Translational Accuracy

10.8K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
10.8K
Types of Genetic Transfer Between Organisms02:18

Types of Genetic Transfer Between Organisms

27.9K
Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
27.9K
Combinatorial Gene Control02:33

Combinatorial Gene Control

8.3K
Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
8.3K
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

915
The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
915
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

6.4K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
6.4K
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

3.0K
3.0K

You might also read

Related Articles

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

Sort by
Same author

Evaluation of Anti-Inflammatory Activity of the New Cardiotonic Steroid γ-Benzylidene Digoxin 8 (BD-8) in Mice.

Cells·2024
Same author

Genome-Scale Analyses Reveal Roadblocks to Monkey Cloning.

Cellular reprogramming·2024
Same author

Reference genes for gene expression profiling in mouse models of <i>Listeria monocytogenes</i> infection.

BioTechniques·2023
Same author

Cloning by SCNT: Integrating Technical and Biology-Driven Advances.

Methods in molecular biology (Clifton, N.J.)·2023
Same author

Cellular responses and microRNA profiling in bovine spermatozoa under heat shock.

Reproduction (Cambridge, England)·2022
Same author

MYC integrates FSH signalling networks in cumulus cells during bovine oocyte maturation.

Acta veterinaria Hungarica·2022

Related Experiment Video

Updated: Jul 7, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K

Gene Regulatory Networks: Improving Inferences with Transfer Learning.

Marcelo Tigre Moura1

  • 1Departamento de Biologia Celular e Molecular, Centro de Biotecnologia, Universidade Federal da Paraíba (UFPB), João Pessoa, Brasil.

Cellular Reprogramming
|December 22, 2023
PubMed
Summary

Deep transfer learning enhances gene regulatory network inference in human cells. This approach identifies disease genes and potential drug targets for heart disease.

Keywords:
deep learninggene networksmachine learningsingle-cell RNA-seqtranscription networks

More Related Videos

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

761
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.9K

Related Experiment Videos

Last Updated: Jul 7, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

761
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.9K

Area of Science:

  • Genomics
  • Computational Biology
  • Systems Biology

Background:

  • Gene regulatory networks (GRNs) are crucial for cellular function and development.
  • Inferring GRNs from high-throughput data is computationally challenging.
  • Human heart disease involves complex genetic and network dysregulations.

Discussion:

  • Deep transfer learning (DTL) offers a powerful framework for improving GRN inference.
  • DTL models can leverage knowledge from related biological systems to enhance predictions.
  • Accurate GRN inference is essential for understanding disease mechanisms.

Key Insights:

  • DTL significantly improves the accuracy of GRN inference in human cells.
  • The method successfully identifies genes associated with human heart disease.
  • Network-based targets for potential drug discovery in heart disease were pinpointed.

Outlook:

  • DTL has broad applicability for GRN inference across various cell types and diseases.
  • Further refinement of DTL models could accelerate precision medicine approaches.
  • This work paves the way for novel therapeutic strategies targeting GRN dysfunctions.