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Related Concept Videos

What is Gene Expression?01:42

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?01:42

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...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Reporter Genes02:11

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.
Commonly used reporter...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
What is Gene Expression?01:36

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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Related Experiment Video

Updated: Jul 1, 2026

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
12:44

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Predicting gene expression from sequence.

Michael A Beer1, Saeed Tavazoie

  • 1Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.

Cell
|April 16, 2004
PubMed
Summary
This summary is machine-generated.

This study introduces a genome-wide method to decode gene expression rules, accurately predicting gene patterns by analyzing DNA sequences and regulatory elements. The approach reveals complex logic governing gene regulation in yeast and worms.

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Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

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Related Experiment Videos

Last Updated: Jul 1, 2026

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
11:34

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Published on: August 9, 2019

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Genomics and Systems Biology
  • Computational Biology and Bioinformatics

Background:

  • Gene expression is regulated by complex combinatorial codes involving DNA sequence elements.
  • Understanding these regulatory rules is crucial for deciphering cellular behavior and function.

Purpose of the Study:

  • To develop and apply a systematic, genome-wide approach for learning the combinatorial gene regulatory code.
  • To identify DNA sequence elements and their constraints that dictate context-dependent transcriptional regulation.
  • To predict gene expression patterns using inferred regulatory rules.

Main Methods:

  • A probabilistic, genome-wide approach was employed to identify local DNA sequence elements.
  • Analysis focused on positional and combinatorial constraints of these elements in transcriptional regulation.
  • Microarray expression data and upstream gene sequences were utilized for prediction modeling.

Main Results:

  • The inferred regulatory rules achieved 73% accuracy in predicting gene expression patterns in Saccharomyces cerevisiae.
  • The system identified predictive regulatory elements and combinatorial rules governing temporal gene expression in Caenorhabditis elegans.
  • Complex logic (AND, OR, NOT) with constraints on motif strength, orientation, and position was required for successful prediction.

Conclusions:

  • This systematic approach successfully deciphers the combinatorial code of gene expression.
  • The framework provides a predictive model for understanding gene regulation from genomic sequence.
  • It generates numerous hypotheses for experimental validation, advancing the study of cellular dynamics.