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Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference

Biological processes are highly dynamic but the current representation of molecular networks is static and largely qualitative. To investigate the dynamic property of genetic networks, a novel quantitative high-throughput method based on RNA interference and capable of calculating the relevance of e...

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Detalles Bibliográficos
Autor principal: Fortunato, Angelo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4443778/
https://www.ncbi.nlm.nih.gov/pubmed/19059334
http://dx.doi.org/10.1016/j.ygeno.2008.11.006
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author Fortunato, Angelo
author_facet Fortunato, Angelo
author_sort Fortunato, Angelo
collection PubMed
description Biological processes are highly dynamic but the current representation of molecular networks is static and largely qualitative. To investigate the dynamic property of genetic networks, a novel quantitative high-throughput method based on RNA interference and capable of calculating the relevance of each interaction, was developed. With this approach, it will be possible to identify not only the components of a network, but also to investigate quantitatively how network and biological processes react to perturbations. As a first application of this method, the genetic interactions of a weak loss-of-function mutation in the gene efl-1/E2F with all the genes of chromosome III were investigated during embryonic development of Caenorhabditis elegans. Fifteen synthetic genetic interactions of efl-1/E2F with the genes of chromosome III were detected, measured and ranked by statistical relevance.
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spelling pubmed-44437782015-05-29 Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference Fortunato, Angelo Genomics Method Biological processes are highly dynamic but the current representation of molecular networks is static and largely qualitative. To investigate the dynamic property of genetic networks, a novel quantitative high-throughput method based on RNA interference and capable of calculating the relevance of each interaction, was developed. With this approach, it will be possible to identify not only the components of a network, but also to investigate quantitatively how network and biological processes react to perturbations. As a first application of this method, the genetic interactions of a weak loss-of-function mutation in the gene efl-1/E2F with all the genes of chromosome III were investigated during embryonic development of Caenorhabditis elegans. Fifteen synthetic genetic interactions of efl-1/E2F with the genes of chromosome III were detected, measured and ranked by statistical relevance. Academic Press 2009-04 /pmc/articles/PMC4443778/ /pubmed/19059334 http://dx.doi.org/10.1016/j.ygeno.2008.11.006 Text en © 2008 Elsevier Inc. All rights reserved.
spellingShingle Method
Fortunato, Angelo
Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title_full Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title_fullStr Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title_full_unstemmed Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title_short Quantitative high-throughput analysis of synthetic genetic interactions in Caenorhabditis elegans by RNA interference
title_sort quantitative high-throughput analysis of synthetic genetic interactions in caenorhabditis elegans by rna interference
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4443778/
https://www.ncbi.nlm.nih.gov/pubmed/19059334
http://dx.doi.org/10.1016/j.ygeno.2008.11.006
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