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

Rate-Determining Steps03:08

Rate-Determining Steps

36.8K
Relating Reaction Mechanisms
In a multistep reaction mechanism, one of the elementary steps progresses significantly slower than the others. This slowest step is called the rate-limiting step (or rate-determining step). A reaction cannot proceed faster than its slowest step, and hence, the rate-determining step limits the overall reaction rate.
The concept of rate-determining step can be understood from the analogy of a 4-lane freeway with a short-stretch of traffic-bottleneck caused due to...
36.8K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

496
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
496
Steps in the Modeling Process01:14

Steps in the Modeling Process

647
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
647
Multi-Step Reactions02:31

Multi-Step Reactions

8.7K
Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
8.7K
Steps for Free-Body Diagram01:22

Steps for Free-Body Diagram

3.2K
When it comes to studying the behavior of objects in mechanics, one of the most important tools available is the free-body diagram. Consider a simple example of a system of two blocks coupled by a massless string over a frictionless pulley. Block 1 is sliding over a table pulled by block 2 as block 2 falls under gravity.
To find the acceleration of the system, it is first necessary to calculate the net force on the system. In order to accomplish this, a free-body diagram can be created to...
3.2K
Energy-releasing Steps of Glycolysis01:28

Energy-releasing Steps of Glycolysis

146.4K
Glycolysis is divided into two phases based on whether energy is utilized or released. While the first phase consumes ATP, the second phase produces energy in the form of ATP and NADH. The energy is released over a sequence of reactions that turns G3P into pyruvate. The energy-releasing phase—steps 6-10 of glycolysis—occurs twice, once for each of the two 3-carbon sugars produced during steps 1-5 of the first phase.
The first energy-releasing step—the 6th step of glycolysis...
146.4K

You might also read

Related Articles

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

Sort by
Same author

Regulatory elements in the Sox9 locus license the initiation of pancreatic ductal adenocarcinoma.

Cell reports·2026
Same author

Endometrial immune markers are upregulated in the proliferative and secretory phases in recurrent pregnancy loss.

Journal of reproductive immunology·2026
Same author

Microenvironmental acidosis drives PARP- and ATM inhibitor resistance in p53 deficient pancreatic cancer.

iScience·2026
Same author

pH-Dependent Microenvironmental Ionic Signaling in Pancreatic Ductal Adenocarcinoma.

Acta physiologica (Oxford, England)·2026
Same author

JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models.

Nucleic acids research·2025
Same author

Upregulation of immune genes in the proliferative phase endometrium enables classification into women with recurrent pregnancy loss versus controls.

Human reproduction (Oxford, England)·2025
Same journal

Sentiment Analysis of Acceptance TVET Online Courses on the Skill Academy App from Google Play: Leveraging Text Mining with Comparison Machine Learning Model.

F1000Research·2026
Same journal

Emotional intelligence: An important skill to learn now more than ever.

F1000Research·2026
Same journal

East Mediterranean Lineage of <i>Brucella melitensis</i> in Human Isolates and Milk Samples in Oman Using MLVA-14.

F1000Research·2026
Same journal

Application of K-Means Clustering for Job Applicant Analysis in Construction Firms Using R.

F1000Research·2026
Same journal

The influence of self-esteem and emotional intelligence on addiction to social networks in Peruvian university students.

F1000Research·2026
Same journal

A Bibliometric Analysis of Music's Role in Promoting Well-Being in Health Science Research.

F1000Research·2026
See all related articles

Related Experiment Video

Updated: Jan 21, 2026

A Step-by-Step Guide to Mosquito Electroantennography
06:39

A Step-by-Step Guide to Mosquito Electroantennography

Published on: March 10, 2021

6.0K

A step-by-step guide to analyzing CAGE data using R/Bioconductor.

Malte Thodberg1,2, Albin Sandelin1,2

  • 1Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.

F1000Research
|July 23, 2019
PubMed
Summary
This summary is machine-generated.

This study presents a case study using the CAGEfightR package for comprehensive Cap Analysis of Gene Expression (CAGE) data analysis. It details methods for identifying, quantifying, and analyzing Transcription Start Sites (TSSs) and enhancers.

Keywords:
CAGEDEEnhancerMotifsPromoterTSS

More Related Videos

Step-by-Step Stapedotomy through Transcanal Exclusive Endoscopic Approach
09:20

Step-by-Step Stapedotomy through Transcanal Exclusive Endoscopic Approach

Published on: March 5, 2022

5.9K
A Step by Step Protocol for Subretinal Surgery in Rabbits
12:31

A Step by Step Protocol for Subretinal Surgery in Rabbits

Published on: September 13, 2016

16.0K

Related Experiment Videos

Last Updated: Jan 21, 2026

A Step-by-Step Guide to Mosquito Electroantennography
06:39

A Step-by-Step Guide to Mosquito Electroantennography

Published on: March 10, 2021

6.0K
Step-by-Step Stapedotomy through Transcanal Exclusive Endoscopic Approach
09:20

Step-by-Step Stapedotomy through Transcanal Exclusive Endoscopic Approach

Published on: March 5, 2022

5.9K
A Step by Step Protocol for Subretinal Surgery in Rabbits
12:31

A Step by Step Protocol for Subretinal Surgery in Rabbits

Published on: September 13, 2016

16.0K

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Cap Analysis of Gene Expression (CAGE) is a widely used 5'-end sequencing technique.
  • CAGE enables the identification and quantification of Transcription Start Sites (TSSs) and enhancers in a single experiment.

Purpose of the Study:

  • To provide a case study demonstrating the use of the CAGEfightR package for orchestrating CAGE data analysis within the Bioconductor project.
  • To outline a workflow for comprehensive CAGE data analysis, from basic identification to advanced interaction analysis.

Main Methods:

  • Utilizing the CAGEfightR package for analysis of CAGE data, starting from BigWig files.
  • Implementing R-code for identifying, quantifying, and annotating TSSs and enhancers.
  • Performing advanced analyses including TSS-enhancer pair identification, enhancer clustering, differential expression analysis, and alternative TSS usage.

Main Results:

  • The workflow successfully integrates basic and advanced CAGE analyses.
  • The study provides a reproducible R-code framework for CAGE data analysis.
  • Guidelines are established for future CAGE studies.

Conclusions:

  • The CAGEfightR package offers a robust platform for comprehensive CAGE data analysis.
  • This workflow facilitates detailed investigation of gene expression regulation through TSSs and enhancers.
  • The study serves as a valuable resource for researchers conducting CAGE-based studies.