Gene Expression Analysis
Gene Expression Analysis - Related Videos
10:34
Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
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Cited by 2 •
2010
This procedure describes a quick and easy workflow to introduce siRNA into difficult to transfect cell lines and follow gene expression by real-time PCR. Use of an automated cell counter, multi-well electroporation plate, and automated electrophoresis station provide quick and reliable results without the need for expensive robotic handling.
29:41
Bacterial Gene Expression Analysis Using Microarrays
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Cited by 3 •
2007
01:42
What is Gene Expression?
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2019
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...
11:03
An Overview of Gene Expression
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2023
Gene expression is the complex process where a cell uses its genetic information to make functional products. This process is regulated at multiple stages, and any misregulation could lead to diseases such as cancer. This video highlights important historical discoveries relating to gene expression, including the understanding of how distinct combinations of DNA bases encode the amino acids that make up proteins. Key questions in the field of gene expression research are explored, followed by a...
13:14
Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
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Cited by 3 •
2009
Gene microarrays are powerful tools in gene expression profiling at a genome-wide level. This technology has application in a variety of biological disciplines including developmental biology and toxicology. In this video, we detail a protocol for global gene expression analysis using a comprehensive oligonucleotide microarray platform for the zebrafish.
FAQs
Comparing transcript abundance across conditions shows which genes change activity when cells encounter different signals or states. Increased or decreased RNA levels can identify differentially expressed genes, while coordinated changes across multiple genes may reveal regulatory patterns. This approach helps connect environmental responses, cellular differentiation, disease-related changes, and treatment effects with underlying molecular mechanisms.
Gene activity can vary according to environmental signals, developmental status, disease, or treatment exposure. Examining these variables allows researchers to distinguish expression patterns associated with particular biological conditions rather than viewing gene activity in isolation. The resulting comparisons can clarify how cells respond, differentiate, or change state and can highlight mechanisms associated with those transitions.
Reverse transcription quantitative PCR and RNA sequencing are two approaches for measuring RNA produced during transcription. Their inclusion in gene expression analysis supports comparisons of transcript abundance between biological conditions, although the methods provide different measurement strategies. Researchers select between them according to the expression question being examined, such as evaluating particular changes or characterizing broader transcriptional patterns.
A basic workflow begins by defining the biological conditions or cell states to compare, followed by measuring the RNA produced during transcription. Researchers then examine transcript abundance to identify genes that differ between those conditions and interpret coordinated patterns in relation to cellular function or regulation. The analysis can ultimately support investigation of mechanisms, disease changes, or treatment responses.
Researchers use this approach when they need to characterize how cells respond to environmental signals, differentiate during development, change during disease, or react to treatment. It can also support the investigation of molecular mechanisms and the search for biomarkers or therapeutic targets. These applications make expression comparisons useful for linking cellular behavior with changes in transcriptional activity.
The results can identify differentially expressed genes as well as broader regulatory patterns associated with a biological condition. Interpreting these findings in their cellular or tissue context can help characterize cellular states and investigate molecular mechanisms. Expression patterns may also suggest candidate biomarkers or therapeutic targets, extending the analysis from measurement toward biological interpretation and application.