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Related Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Protein Networks

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Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...
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.
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Chromatin Structure and RNA Splicing02:41

Chromatin Structure and RNA Splicing

In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...

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Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
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Published on: September 25, 2021

Algorithm to identify frequent coupled modules from two-layered network series: application to study transcription

Wenyuan Li1, Chao Dai, Chun-Chi Liu

  • 1Program in Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|June 16, 2012
PubMed
Summary

This study introduces a novel computational method to analyze coupled biological networks, revealing insights into transcription-splicing modules and their cellular functions.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Genomics

Background:

  • Cellular organization involves interconnected multi-layer biological networks, including transcriptional regulatory networks and splicing regulatory networks.
  • Understanding the interplay between these different network types is crucial for deciphering cellular functions and mechanisms.
  • Existing network analysis methods typically focus on single network types, limiting the study of cross-network interactions.

Purpose of the Study:

  • To develop the first computational method for pattern mining across coupled, two-layered biological networks.
  • To identify frequent coupled clusters between different types of biological networks.
  • To explore the extent, cellular functions, and mechanisms of transcription-splicing coupling.

Main Methods:

  • Formulated the problem of identifying frequent coupled clusters as a tensor-based computation.
  • Developed an efficient computational solution for analyzing two-layered biological networks.
  • Applied the method to 38 two-layered co-transcription and co-splicing networks derived from RNA-seq data.

Main Results:

  • Identified an atlas of coupled transcription-splicing modules.
  • Provided insights into the mechanisms and extent of transcription-splicing coupling.
  • Demonstrated the utility of the tensor-based computational approach for multi-network analysis.

Conclusions:

  • The developed method enables novel pattern mining across coupled biological networks.
  • The findings offer a deeper understanding of transcription-splicing coordination in cellular activities.
  • This approach facilitates the exploration of complex regulatory mechanisms in systems biology.