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Experimental RNAi

Experimental RNAi

RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...

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Related Experiment Video

Updated: May 12, 2026

RNA Interference in Aquatic Beetles as a Powerful Tool for Manipulating Gene Expression at Specific Developmental Time Points

RNA Interference in Aquatic Beetles as a Powerful Tool for Manipulating Gene Expression at Specific Developmental Time Points

Published on: May 29, 2020

Learning gene network structure from time laps cell imaging in RNAi Knock downs.

Henrik Failmezger¹, Paurush Praveen, Achim Tresch

¹Computational Biology and Regulatory Networks, Max-Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Cologne, Germany.

Bioinformatics (Oxford, England)

|April 19, 2013

Summary

This summary is machine-generated.

This study introduces a novel method to infer gene networks using cell microscopy data. The approach accurately reconstructs gene interactions from phenotypic changes, offering a new tool for systems biology research.

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MISSION esiRNA for RNAi Screening in Mammalian Cells

MISSION esiRNA for RNAi Screening in Mammalian Cells

Published on: May 12, 2010

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Last Updated: May 12, 2026

RNA Interference in Aquatic Beetles as a Powerful Tool for Manipulating Gene Expression at Specific Developmental Time Points

RNA Interference in Aquatic Beetles as a Powerful Tool for Manipulating Gene Expression at Specific Developmental Time Points

Published on: May 29, 2020

Combining Optogenetics with Artificial microRNAs to Characterize the Effects of Gene Knockdown on Presynaptic Function within Intact Neuronal Circuits

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MISSION esiRNA for RNAi Screening in Mammalian Cells

MISSION esiRNA for RNAi Screening in Mammalian Cells

Published on: May 12, 2010

Area of Science:

Computational Biology
Systems Biology
Genomics

Background:

RNA interference (RNAi) is a key tool for gene perturbation.
Computational methods are vital for understanding biological networks from RNAi data.
Existing methods primarily rely on gene expression data, overlooking other data types.

Purpose of the Study:

To develop a novel computational method for inferring gene networks.
To utilize high-dimensional phenotypic perturbation effects from single-cell microscopy data.
To explore alternative data types beyond gene expression for network reconstruction.

Main Methods:

Employing time-lapse microscopy to record phenotypic effects of gene perturbations.
Extracting cell shape, intensity, and texture features.
Aligning cell cycle time and applying Dynamic Nested Effects Models (dynoNEMs) with Markov Chain Monte Carlo.
Utilizing the Bioconductor R-package 'nem' for dynoNEMs implementation.

Main Results:

Successfully inferred gene networks from high-dimensional phenotypic data.
Demonstrated high reconstruction quality through simulation studies.
Validated a network reconstruction from 22 gene knockdowns, with all inferred edges supported by literature.

Conclusions:

The developed method offers a robust approach for gene network inference using phenotypic data.
This technique expands the toolkit for systems biology by leveraging microscopy-derived features.
The findings highlight the potential of phenotypic data in uncovering complex gene interactions.