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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...

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...

What is Gene Expression?

What is Gene Expression?

Reporter Genes

Reporter Genes

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.

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...

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Related Experiment Video

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In vivo Application of the REMOTE-control System for the Manipulation of Endogenous Gene Expression

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Published on: March 29, 2019

Reverse engineering of gene regulatory network using restricted gene expression programming.

Bin Yang¹, Sanrong Liu¹, Wei Zhang¹

¹1 School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277160, China.

Journal of Bioinformatics and Computational Biology

|June 25, 2016

Summary

This summary is machine-generated.

We developed a new method, restricted gene expression programming (RGEP), to infer gene regulatory networks. This approach, combined with a hybrid evolutionary algorithm, shows improved performance over existing popular methods for systems biology.

Keywords:

Gene regulatory network cuckoo search gene expression programming hybrid evolutionary

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Area of Science:

Systems biology
Computational biology
Bioinformatics

Background:

Gene regulatory network inference is crucial for understanding cellular mechanisms.
Traditional methods face challenges in accurately modeling complex biological systems.

Purpose of the Study:

To introduce a novel S-system model representation called restricted gene expression programming (RGEP).
To develop a hybrid evolutionary algorithm for optimizing gene regulatory network models.

Main Methods:

Utilized restricted gene expression programming (RGEP) for gene regulatory network inference.
Employed a hybrid evolutionary algorithm combining structure-based evolutionary algorithm and cuckoo search (CS).
Validated the method on synthetic and real biological datasets (E. coli SOS DNA repair network).

Main Results:

The proposed RGEP method demonstrated superior performance in inferring gene regulatory networks.
The hybrid evolutionary algorithm effectively optimized both model architecture and parameters.
Achieved better results compared to previously established popular methods.

Conclusions:

RGEP offers a powerful new approach for gene regulatory network inference.
Hybrid evolutionary algorithms enhance the accuracy and efficiency of systems biology modeling.
The method shows significant potential for advancing the field of computational biology.