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Mechanism of Ciliary Motion01:05

Mechanism of Ciliary Motion

The ciliary structures were first seen in 1647 by Antonie Leeuwenhoek while observing the protozoans. In lower organisms, these appendages are responsible for cell movement, while in higher organisms, these appendages help in the movement of the extracellular fluids within the body cavities.
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Artificial Intelligence Approaches to Assessing Primary Cilia
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Published on: May 1, 2021

Finding ciliary genes: a computational approach.

Johan Henriksson1, Brian P Piasecki, Kristina Lend

  • 1Department of Biosciences and Nutrition, Center for Biosciences at NOVUM, Karolinska Institute, Huddinge, Sweden. mahogny@areta.org

Methods in Enzymology
|March 26, 2013
PubMed
Summary
This summary is machine-generated.

Researchers developed a computational method to find new ciliary genes by searching for specific DNA sequences (X-boxes) regulated by Regulatory Factor binding to the X-box (RFX) transcription factors. This approach aids in understanding gene regulation across species.

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Area of Science:

  • Genetics
  • Computational Biology
  • Molecular Biology

Background:

  • Many ciliary genes in animals like C. elegans are controlled by Regulatory Factor binding to the X-box (RFX) transcription factors.
  • RFX transcription factors bind to X-box promoter motifs to directly regulate ciliary gene expression.

Purpose of the Study:

  • To present a computational approach for identifying novel ciliary gene candidates genome-wide.
  • To utilize the X-box promoter motif as a key search parameter for discovering ciliary genes.

Main Methods:

  • Genome-wide identification and extraction of genes and promoter sequences.
  • Searching promoters for regulatory sequence elements using known instances as training sets.
  • Scoring, sorting, and outputting candidate genes and promoters based on identified elements, incorporating evolutionary conservation.

Main Results:

  • A computational pipeline was developed to systematically search for genes regulated by specific promoter motifs.
  • The approach successfully identifies candidate genes and their associated regulatory elements.
  • Evolutionary conservation is leveraged to strengthen the reliability of identified gene candidates.

Conclusions:

  • The presented computational approach offers a powerful tool for discovering novel ciliary genes.
  • The modular design allows for broad applications in identifying conserved gene regulation across various gene groups.
  • This method facilitates a deeper understanding of transcriptional regulation in diverse animal species.