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Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

Regulation of Expression at Multiple Steps

Regulation of Expression at Multiple Steps

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 addition of a...

Downsampling

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...

What is Gene Expression?

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...

What is Gene Expression?

What is Gene Expression?

A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then processed and...

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Updated: Jun 2, 2026

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

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

Published on: December 7, 2021

Discretization provides a conceptually simple tool to build expression networks.

J Keith Vass¹, Desmond J Higham, Manikhandan A V Mudaliar

¹Translational Medicine Research Collaboration Institute, University of Dundee, Ninewells Hospital, Dundee, United Kingdom. keithvass13@gmail.com

|May 3, 2011

Summary

This study introduces a novel gene expression analysis method using discretized data to identify gene cliques and stratify patients for biomarker discovery. The approach enhances understanding of gene co-regulation patterns and their relevance in biological samples.

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

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Area of Science:

Computational biology
Systems biology
Bioinformatics

Background:

Biomarker identification relies on co-expression patterns and patient stratification algorithms.
Existing methods may oversimplify complex gene relationships.

Purpose of the Study:

To develop a biologically intuitive discretization technique for gene expression data.
To create a simple algorithm for ranking gene-set relevance in patients.
To improve the identification of co-regulated and anti-regulated genes and associated patient samples.

Main Methods:

Explored a discretization technique coding genes as up-regulated, down-regulated, or unchanged relative to the mean.
Utilized synthetic microarray data (SynTReN) to validate the method's accuracy in identifying known gene interactions.
Applied the method to real-world gene expression data from white blood cells and cell lines, comparing it with correlation-based methods.

Main Results:

The discretization method provides a richer description of gene relationships than standard correlation.
Successfully identified known gene interactions in synthetic data, demonstrating high accuracy.
Differentiated positive co-regulation into 'up-together' and 'down-together', and negative co-regulation as directed 'up-down' relationships.
Observed directional relationships in real data not present in synthetic data.

Conclusions:

The proposed discretization method effectively identifies gene cliques and stratifies patients for biomarker discovery.
This approach enhances the analysis of gene co-regulation and anti-regulation, aiding in the dissection of gene-sample relationships.
The method offers a valuable tool for identifying relevant gene sets and patient subgroups in complex biological datasets.