SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.
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ABSTRACT:
SUBMITTER: Ko E
PROVIDER: S-EPMC11133003 | biostudies-literature | 2024 May
REPOSITORIES: biostudies-literature
Publications
SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.
Ko Euiseong E Kim Youngsoon Y Shokoohi Farhad F Mersha Tesfaye B TB Kang Mingon M
Briefings in bioinformatics 20240501 4
Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases. However, most genetic and clinical outcome studies are designed in sex-combined framework considering sex as a covariate. Few sex-specific studies have analyzed males and females separately, which failed to identify gene-by-sex interaction. Here, we propose a novel unified biologically interpretable deep learning-based framework (named SPIN) for sexual dimorphism analysis. We demonstrate that SP ...[more]
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