Machine learning analysis identifies 50 conserved genes in both Drosophila fruit flies and humans strongly associated with neurological aging, suggesting potential for further aging-related studies using fruit flies as a model organism.
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Article Title: Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive
Funding: EMM was supported by a Iowa State University College of Human Sciences Grant, JLW was supported by an NSF GFRP. In all cases, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.
Competing Interests: The authors have declared that no competing interests exist.
Article URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255085
PLOS ONE
Experimental study
People
Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive
11-Aug-2021
The authors have declared that no competing interests exist.