Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach.

ABSTRACT:

Background

Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases. The diagnosis of COPD is generally based on the pulmonary function testing, however, difficulties underlie in prognosis of smokers or early stage of COPD patients due to the complexity and heterogeneity of the pathogenesis. Computational analyses of omics technologies are expected as one of the solutions to resolve such complexities.

Methods

We obtained transcriptomic data by in vitro testing with exposures of human bronchial epithelial cells to the inducers for early events of COPD to identify the potential descriptive marker genes. With the identified genes, the machine learning technique was employed with the publicly available transcriptome data obtained from the lung spe

SUBMITTER: Matsumura K 

PROVIDER: S-EPMC6998147 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature