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Gene Targeting in Disease Networks
Profiling of whole transcriptomes has become a cornerstone of molecular biology and an invaluable tool for the characterization of clinical phenotypes and the identification of disease subtypes. Analyses of these data are becoming ever more sophisticated as we move beyond simple comparisons to consi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103030/ https://www.ncbi.nlm.nih.gov/pubmed/33968133 http://dx.doi.org/10.3389/fgene.2021.649942 |
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author | Weighill, Deborah Ben Guebila, Marouen Glass, Kimberly Platig, John Yeh, Jen Jen Quackenbush, John |
author_facet | Weighill, Deborah Ben Guebila, Marouen Glass, Kimberly Platig, John Yeh, Jen Jen Quackenbush, John |
author_sort | Weighill, Deborah |
collection | PubMed |
description | Profiling of whole transcriptomes has become a cornerstone of molecular biology and an invaluable tool for the characterization of clinical phenotypes and the identification of disease subtypes. Analyses of these data are becoming ever more sophisticated as we move beyond simple comparisons to consider networks of higher-order interactions and associations. Gene regulatory networks (GRNs) model the regulatory relationships of transcription factors and genes and have allowed the identification of differentially regulated processes in disease systems. In this perspective, we discuss gene targeting scores, which measure changes in inferred regulatory network interactions, and their use in identifying disease-relevant processes. In addition, we present an example analysis for pancreatic ductal adenocarcinoma (PDAC), demonstrating the power of gene targeting scores to identify differential processes between complex phenotypes, processes that would have been missed by only performing differential expression analysis. This example demonstrates that gene targeting scores are an invaluable addition to gene expression analysis in the characterization of diseases and other complex phenotypes. |
format | Online Article Text |
id | pubmed-8103030 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81030302021-05-08 Gene Targeting in Disease Networks Weighill, Deborah Ben Guebila, Marouen Glass, Kimberly Platig, John Yeh, Jen Jen Quackenbush, John Front Genet Genetics Profiling of whole transcriptomes has become a cornerstone of molecular biology and an invaluable tool for the characterization of clinical phenotypes and the identification of disease subtypes. Analyses of these data are becoming ever more sophisticated as we move beyond simple comparisons to consider networks of higher-order interactions and associations. Gene regulatory networks (GRNs) model the regulatory relationships of transcription factors and genes and have allowed the identification of differentially regulated processes in disease systems. In this perspective, we discuss gene targeting scores, which measure changes in inferred regulatory network interactions, and their use in identifying disease-relevant processes. In addition, we present an example analysis for pancreatic ductal adenocarcinoma (PDAC), demonstrating the power of gene targeting scores to identify differential processes between complex phenotypes, processes that would have been missed by only performing differential expression analysis. This example demonstrates that gene targeting scores are an invaluable addition to gene expression analysis in the characterization of diseases and other complex phenotypes. Frontiers Media S.A. 2021-04-23 /pmc/articles/PMC8103030/ /pubmed/33968133 http://dx.doi.org/10.3389/fgene.2021.649942 Text en Copyright © 2021 Weighill, Ben Guebila, Glass, Platig, Yeh and Quackenbush. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Weighill, Deborah Ben Guebila, Marouen Glass, Kimberly Platig, John Yeh, Jen Jen Quackenbush, John Gene Targeting in Disease Networks |
title | Gene Targeting in Disease Networks |
title_full | Gene Targeting in Disease Networks |
title_fullStr | Gene Targeting in Disease Networks |
title_full_unstemmed | Gene Targeting in Disease Networks |
title_short | Gene Targeting in Disease Networks |
title_sort | gene targeting in disease networks |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103030/ https://www.ncbi.nlm.nih.gov/pubmed/33968133 http://dx.doi.org/10.3389/fgene.2021.649942 |
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