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Related Concept Videos

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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...
Regulation of Expression at Multiple Steps01:23

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...
Regulation of Expression Occurs at Multiple Steps02:24

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 Steps02:24

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...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...

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Related Experiment Video

Updated: Jun 21, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

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

Published on: December 7, 2021

Reconstruct gene regulatory network using slice pattern model.

Yadong Wang1, Guohua Wang, Bo Yang

  • 1School of Computer Science and Technology, Harbin Institute of Technology, Heilongjiang, PR China. ydwang@hit.edu.cn

BMC Genomics
|July 15, 2009
PubMed
Summary
This summary is machine-generated.

The Slice Pattern Model (SPM) enhances gene regulatory network inference from noisy gene expression data. SPM reconstructs more stable and reliable networks compared to traditional linear models.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Gene expression time series data is valuable for studying gene functions and interactions.
  • Existing linear models struggle with noise and nonlinear relationships in gene expression data.
  • Accurate inference of gene regulatory models from expression data remains a challenge.

Purpose of the Study:

  • To present a novel model-based computational approach, the Slice Pattern Model (SPM).
  • To identify gene regulatory networks from time series gene expression data.
  • To improve the stability and reliability of gene regulatory model inference.

Main Methods:

  • Utilized a model-based computational approach called Slice Pattern Model (SPM).
  • Employed pattern recognition and similarity analysis to mitigate noise effects.
  • Integrated a genetic algorithm for optimizing gene network model parameters.

Main Results:

  • SPM accurately reconstructs gene networks, handling multiple transcriptional time lags.
  • Applied to yeast cell cycle data, SPM identified 18 gene relationships at a 55% reliability threshold.
  • The identified gene relationships largely align with findings from previous studies.

Conclusions:

  • SPM effectively limits the impact of noise through pattern recognition and similarity analysis.
  • Genetic algorithms enhance the optimization of gene network model parameters within SPM.
  • SPM-reconstructed gene regulatory models demonstrate superior stability and reliability over traditional linear models.