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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...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
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...
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein.

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Related Experiment Video

Updated: Jul 4, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

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Gene regulatory network reconstruction using conditional mutual information.

Kuo-Ching Liang1, Xiaodong Wang

  • 1Department of Electrical Engineering, Columbia University, New York, NY 10027, USA.

EURASIP Journal on Bioinformatics & Systems Biology
|June 28, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new gene regulatory network inference method using mutual and conditional mutual information. The approach effectively identifies complex gene interactions like co-regulation and interactive regulation.

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Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets
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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Gene regulatory network inference from expression data is crucial for understanding biological systems.
  • Relevance-network approaches offer scalable solutions but often miss complex interactions like co-regulation.

Purpose of the Study:

  • To develop an improved relevance network model for gene regulatory network inference.
  • To enhance the detection of direct, interactive, and co-regulatory gene interactions.

Main Methods:

  • Utilized both mutual information and conditional mutual information for gene interaction detection.
  • Developed a novel conditional mutual information estimator based on adaptive partitioning.
  • The estimator handles both discrete and continuous random variables for accurate conditioning.

Main Results:

  • The proposed model successfully infers gene regulatory networks.
  • Demonstrated superior performance in identifying networks with co-regulated and interactively regulated genes.
  • The adaptive partitioning estimator proved effective for complex interaction analysis.

Conclusions:

  • The novel relevance network model enhances gene regulatory network inference.
  • Conditional mutual information is key to uncovering complex gene interactions.
  • This method offers improved insights into the functional organization of biological systems.