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

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

9.8K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
9.8K
Reporter Genes02:11

Reporter Genes

11.2K
Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
11.2K
Master Transcription Regulators02:23

Master Transcription Regulators

6.9K
Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
6.9K
Genetic Screens02:46

Genetic Screens

4.9K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.9K
Repressible Operon: trp Operon01:21

Repressible Operon: trp Operon

3
The trp operon in Escherichia coli exemplifies a repressible operon. It regulates the synthesis of tryptophan through repressor-mediated transcriptional control and attenuation. This dual regulatory mechanism ensures tryptophan biosynthesis occurs only when needed, conserving cellular resources.Structure of the trp OperonThe trp operon consists of five structural genes (trpE, trpD, trpC, trpB, and trpA) that encode enzymes for tryptophan biosynthesis. These genes are transcribed as a single...
3
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

872
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...
872

You might also read

Related Articles

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

Sort by
Same author

PARROT: Phase-Altering Regulatory Rewiring Over Time.

bioRxiv : the preprint server for biology·2026
Same author

LOESS and DE-SWAN can induce artifactual "waves" of molecular aging.

bioRxiv : the preprint server for biology·2026
Same author

Genomic, Transcriptomic, and Regulomic Analyses Do Not Support Profound Autism as a Distinct Biological Category.

bioRxiv : the preprint server for biology·2026
Same author

Deploying a JupyterHub Server for Academic Research Using Netbooks as an Example.

Current protocols·2026
Same author

Leveraging Artificial Intelligence in Allergy, Asthma, and Immunology With Environmental Exposures.

Allergy·2026
Same author

Intrinsic microRNA regulatory programs define lineage-specific differentiation in human mesenchymal stem cells of different origin - dental pulp- and fat tissue-derived.

Stem cell reviews and reports·2026

Related Experiment Video

Updated: Jun 6, 2025

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.3K

Reproducible processing of TCGA regulatory networks.

Viola Fanfani1, Katherine H Shutta1,2, Panagiotis Mandros1

  • 1Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Biorxiv : the Preprint Server for Biology
|November 22, 2024
PubMed
Summary

We developed tcga-data-nf, a Nextflow workflow for reproducible cancer regulatory network analysis from The Cancer Genome Atlas (TCGA) data. This tool integrates multi-omics data to infer gene and protein interactions, aiding disease mechanism discovery.

Keywords:
CancerGene Regulatory NetworkNetworkDataCompanionNextflowThe Cancer Genome Atlasreproducibility

More Related Videos

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

2.1K
Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

1.5K

Related Experiment Videos

Last Updated: Jun 6, 2025

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.3K
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

2.1K
Rapid Development of Cell State Identification Circuits with Poly-Transfection
09:21

Rapid Development of Cell State Identification Circuits with Poly-Transfection

Published on: February 24, 2023

1.5K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Technological advancements enable deep exploration of disease molecular basis.
  • Biological networks are crucial for analyzing omics data and modeling gene/protein interactions.
  • Large projects like The Cancer Genome Atlas (TCGA) provide rich data for computational method development.

Purpose of the Study:

  • To develop a coherent and reusable workflow for end-to-end analysis of cancer regulatory networks.
  • To enable reproducible inference of regulatory networks from TCGA multi-omics data.

Main Methods:

  • Development of tcga-data-nf, a Nextflow workflow.
  • Integration of multi-omics data (RNA-seq, methylation) from TCGA.
  • Utilizing netZoo software tools for regulatory network inference.
  • Leveraging the NetworkDataCompanion R package for data management.

Main Results:

  • The workflow allows reproducible inference of regulatory networks from thousands of TCGA samples via a single command.
  • Demonstrated application in studying epigenetic differences between colon cancer subtypes.
  • Provided pre-generated networks for the 10 most common cancer types.

Conclusions:

  • tcga-data-nf offers a complete, flexible, and extensible framework for cancer regulatory network analysis.
  • The workflow ensures reproducible inference and analysis, addressing a gap in existing software tools.