Incorporating Tissue-Specific Gene Expression Data to Improve Chemical-Disease Inference of in Silico Toxicogenomics Methods.

ABSTRACT: In silico toxicogenomics methods are resource- and time-efficient approaches for inferring chemical-protein-disease associations with potential mechanism information for exploring toxicological effects. However, current in silico toxicogenomics systems make inferences based on only chemical-protein interactions without considering tissue-specific gene/protein expressions. As a result, inferred diseases could be overpredicted with false positives. In this work, six tissue-specific expression datasets of genes and proteins were collected from the Expression Atlas. Genes were then categorized into high, medium, and low expression levels in a tissue- and dataset-specific manner. Subsequently, the tissue-specific expression datasets were incorporated into the chemical-protein-disease inference

SUBMITTER: Wang SS 

PROVIDER: S-EPMC11348041 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature