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What is Gene Expression?01:42

What is Gene Expression?

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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
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Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Reporter Genes02:11

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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What is Gene Expression?01:36

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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...
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Global Regulatory Systems

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Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...
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Related Experiment Video

Updated: Apr 25, 2026

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Published on: February 25, 2017

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Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods.

Karamveer1, Yasin Uzun1,2,3

  • 1Department of Pediatrics, The Pennsylvania State University College of Medicine, Hershey, PA, USA.

Bioinformatics and Biology Insights
|November 6, 2024
PubMed
Summary
This summary is machine-generated.

This study addresses the lack of comprehensive benchmarking for gene regulatory network (GRN) construction methods using single-cell sequencing data. It provides a framework for evaluating these computational approaches, crucial for understanding cell differentiation.

Keywords:
Gene regulatory networksbenchmarkingepigenomicsground truthsingle-cell genomics

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Area of Science:

  • Computational Biology
  • Genomics
  • Systems Biology

Background:

  • Gene regulatory networks (GRNs) model genetic interactions controlling gene expression and cell differentiation.
  • Single-cell sequencing provides high-resolution data for building GRNs.
  • Existing computational methods for GRN construction lack standardized benchmarking.

Purpose of the Study:

  • To provide a comprehensive discussion on benchmarking approaches for gene regulatory network construction from single-cell data.
  • To establish standardized terminology, gold-standard datasets, and performance metrics for evaluating GRN inference methods.

Main Methods:

  • Review and synthesis of existing literature on GRN construction and benchmarking.
  • Definition of GRN terminology and common gold-standard datasets.
  • Identification and analysis of performance metrics for network construction methodologies.

Main Results:

  • Clarification of GRN terminology and common benchmarking datasets.
  • Definition of performance metrics for evaluating GRN inference algorithms.
  • Discussion of advantages and limitations of various benchmarking strategies.

Conclusions:

  • A standardized approach to benchmarking is essential for advancing GRN construction from single-cell data.
  • The study provides a foundation for future method development and comparative analysis.
  • Highlights the need for alternative ground truth datasets and further considerations in benchmarking GRN inference.