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Ligand-gated ion channels are transmembrane proteins that play a vital role in intercellular communication and functions of the nervous system. They allow the influx of ions across the membrane once the neurotransmitter binds, allowing the subsequent transmission of electrical excitation across the neurons. Other ligand-gated ion channels, like the γ-aminobutyric acid (GABA) receptor, permit anions like chloride into the cells on the binding of the GABA molecule. Their entry into the cell...
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Ion channels are specialized proteins on the plasma membrane that allow charged ions to pass down their electrochemical gradient. Their main function is to maintain the membrane potential which is critical for cell viability. These channels are either gated or non-gated and can transport more than a thousand ions within milliseconds for the cellular event to occur.
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ISAC's Gating-ML 2.0 data exchange standard for gating description.

Josef Spidlen1, Wayne Moore2,

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|May 16, 2015
PubMed
Summary

The new Gating-ML 2.0 standard simplifies flow cytometry data analysis by enabling software interoperability for gating. This promotes reproducibility and wider adoption of analytical tools in research.

Keywords:
bioinformaticsdata standardfile formatflow cytometrygating

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Immunology

Background:

  • Software interoperability for flow cytometry gating has been a significant challenge, hindering data analysis reproducibility.
  • The lack of standardized gating formats limits the use of diverse analytical tools and independent verification of results.

Purpose of the Study:

  • To introduce Gating-ML 2.0, a streamlined computer file format for encoding and interchanging flow cytometry gating data.
  • To enhance software interoperability and improve the reproducibility of flow cytometry data analysis.

Main Methods:

  • Development of Gating-ML 2.0 based on community feedback from Gating-ML 1.5.
  • Provision of free, open-source reference implementations, compliance tests, and examples for developers.
  • Extensive theoretical and practical review and testing of the Gating-ML standard.

Main Results:

  • Gating-ML 2.0 offers a significantly simplified format, making it easier for software tools to support.
  • The standard has been approved by ISAC for public deployment, indicating maturity and readiness.
  • Resources provided aim to stimulate commercial adoption and community support.

Conclusions:

  • Gating-ML 2.0 addresses the long-standing bottleneck in flow cytometry data analysis by standardizing gating.
  • The standard is poised for widespread adoption, promising improved reproducibility and collaborative research in cytometry.
  • ISAC encourages community engagement to leverage the benefits of this mature and well-tested standard.