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Allergy, Asthma & Immunology Research ; : 399-411, 2020.
Article in English | WPRIM | ID: wpr-811070

ABSTRACT

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.


Subject(s)
Asthma , Biostatistics , Genetics , Genome , Machine Learning , RNA , Sequence Analysis, RNA , Transcriptome
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