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Regulation of Expression at Multiple Steps01:23

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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...
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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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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.
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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Inferring protein modulation from gene expression data using conditional mutual information.

Federico M Giorgi1, Gonzalo Lopez1, Jung H Woo1

  • 1Department of Systems Biology, Columbia University, New York, New York, United States of America; Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America.

Plos One
|October 15, 2014
PubMed
Summary
This summary is machine-generated.

We developed CINDy, a new computational algorithm to map gene regulatory networks. CINDy accurately identifies causal dependencies between signaling proteins and transcription factors from gene expression data.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Genomics

Background:

  • Dissecting genome-wide causal post-translational regulatory dependencies is a significant challenge in biology.
  • Existing computational algorithms for this task are limited due to the complexity of biological systems.

Purpose of the Study:

  • To introduce CINDy (Conditional Inference of Network Dynamics), a novel algorithm for inferring context-specific, genome-wide regulatory dependencies.
  • To enable the analysis of relationships between signaling protein activity and transcription factor targets using gene expression data.

Main Methods:

  • CINDy employs an adaptive partitioning methodology to precisely estimate Condition Mutual Information (CMI).
  • This approach is specifically designed to analyze the dependencies between transcription factors and their targets, conditioned on signaling protein expression.

Main Results:

  • Conditional Mutual Information (CMI) analysis is demonstrated to be highly effective for dissecting post-translational regulatory dependencies.
  • CINDy significantly outperforms existing methods in sensitivity and precision when validated against known protein-protein interactions in signal transduction networks.

Conclusions:

  • CINDy provides a powerful new tool for high-throughput, genome-wide inference of regulatory networks.
  • The algorithm enhances our ability to understand complex biological regulation at the post-translational level.