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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
What is Gene Expression?01:42

What is Gene Expression?

Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...

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Related Experiment Video

Updated: May 30, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

ExpressionPlot: a web-based framework for analysis of RNA-Seq and microarray gene expression data.

Brad A Friedman1, Tom Maniatis

  • 1Department of Molecular and Cell Biology, Harvard University, 7 Divinity Ave, Cambridge, MA 02138, USA. brad.aaron.friedman@gmail.com

Genome Biology
|July 30, 2011
PubMed
Summary
This summary is machine-generated.

ExpressionPlot is a new software package for analyzing gene expression data from RNA-Sequencing and microarray platforms. It provides tools to visualize and compare gene expression changes in biological samples.

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Last Updated: May 30, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
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Published on: July 29, 2022

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

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Published on: October 11, 2019

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA-Sequencing (RNA-Seq) and microarray platforms are crucial for studying gene expression and RNA processing.
  • Analyzing large-scale gene expression datasets requires robust and user-friendly software tools.

Purpose of the Study:

  • To introduce ExpressionPlot, a novel software package designed for the comprehensive analysis of gene expression data.
  • To provide a biologically centered interface for visualizing and comparing diverse datasets from RNA-Seq and microarray experiments.

Main Methods:

  • Development of a software package with a default back end for raw data preparation (RNA-Seq and Affymetrix microarray).
  • Implementation of a web-based front end for interactive data exploration and visualization.
  • Creation of resources including download/installation guides, a user manual, and a discussion group.

Main Results:

  • ExpressionPlot successfully processes raw RNA-Seq and microarray data.
  • The software offers an intuitive interface for browsing, visualizing, and comparing gene expression datasets.
  • A functional prototype and supporting documentation are available for users.

Conclusions:

  • ExpressionPlot serves as a valuable tool for researchers studying gene expression patterns.
  • The package facilitates the interpretation of complex biological data through enhanced visualization and comparison capabilities.