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Reporter Genes

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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.

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Updated: Aug 9, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene

Yan Zhang¹, Weiyu Shi², Yeqing Sun³

¹College of Environmental Science and Engineering, Dalian Maritime University, 116026, Dalian, Liaoning, China.

|February 16, 2023

Summary

GMIGAGO, a novel gene module identification algorithm, enhances functional and expression similarity. This method effectively identifies biologically significant gene modules and potential therapeutic targets from gene expression data.

Keywords:

Functional gene module Gene expression data Gene ontology Genetic algorithm Overlapping gene module Partitioning around medoids

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Last Updated: Aug 9, 2025

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Published on: June 17, 2012

Area of Science:

Bioinformatics
Computational Biology
Systems Biology

Background:

Genes function in networks, necessitating gene module identification for interpreting expression profiles.
Existing methods often focus on either expression or functional similarity, but not both.

Purpose of the Study:

To propose GMIGAGO, a functional Gene Module Identification algorithm using a Genetic Algorithm and Gene Ontology.
To integrate both functional and expression similarity for improved gene module identification.

Main Methods:

GMIGAGO employs a two-stage approach: initial clustering using Partitioning Around Medoids Based on Genetic Algorithm (PAM-GA) for expression similarity.
Subsequent optimization using Genetic Algorithm for Functional Similarity Optimization (FSO-GA) enhances functional similarity based on Gene Ontology.

Main Results:

GMIGAGO significantly outperformed state-of-the-art algorithms in identifying gene modules with higher functional similarity across six datasets.
Applied to BRCA, THCA, HNSC, COVID-19, Stem, and Radiation datasets, GMIGAGO identified modules with important biological functions.

Conclusions:

GMIGAGO demonstrates excellent performance in uncovering molecular mechanisms and identifying potential biomarkers.
Hub genes within identified modules may serve as therapeutic targets for diseases and radiation protection, aiding precision therapy.