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Understanding the Molecular Mechanisms of Asthma through Transcriptomics

The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approache...

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Detalles Bibliográficos
Autores principales: Park, Heung-Woo, Weiss, Scott T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Asthma, Allergy and Clinical Immunology; The Korean Academy of Pediatric Allergy and Respiratory Disease 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061151/
https://www.ncbi.nlm.nih.gov/pubmed/32141255
http://dx.doi.org/10.4168/aair.2020.12.3.399
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author Park, Heung-Woo
Weiss, Scott T.
author_facet Park, Heung-Woo
Weiss, Scott T.
author_sort Park, Heung-Woo
collection PubMed
description The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approaches provides a quick and effective way of identifying novel genes and pathways related to asthma, which is a heterogeneous disease with diverse pathophysiological mechanisms. In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. Studies reviewed here are classified into 2 classes based on the tissues utilized: blood and airway cells.
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spelling pubmed-70611512020-05-01 Understanding the Molecular Mechanisms of Asthma through Transcriptomics Park, Heung-Woo Weiss, Scott T. Allergy Asthma Immunol Res Review The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approaches provides a quick and effective way of identifying novel genes and pathways related to asthma, which is a heterogeneous disease with diverse pathophysiological mechanisms. In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. Studies reviewed here are classified into 2 classes based on the tissues utilized: blood and airway cells. The Korean Academy of Asthma, Allergy and Clinical Immunology; The Korean Academy of Pediatric Allergy and Respiratory Disease 2020-02-24 /pmc/articles/PMC7061151/ /pubmed/32141255 http://dx.doi.org/10.4168/aair.2020.12.3.399 Text en Copyright © 2020 The Korean Academy of Asthma, Allergy and Clinical Immunology • The Korean Academy of Pediatric Allergy and Respiratory Disease https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Park, Heung-Woo
Weiss, Scott T.
Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title_full Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title_fullStr Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title_full_unstemmed Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title_short Understanding the Molecular Mechanisms of Asthma through Transcriptomics
title_sort understanding the molecular mechanisms of asthma through transcriptomics
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061151/
https://www.ncbi.nlm.nih.gov/pubmed/32141255
http://dx.doi.org/10.4168/aair.2020.12.3.399
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