Hash Brown Taha

The paper analyzes skeletal muscle transcriptomic responses to exercise in humans, mice, and rats to identify conserved and species-specific exerkine regulation patterns.

NANOME improves DNA methylation detection using nanopore long-read sequencing by integrating multiple tools and enhancing precision and accuracy in human cell lines.

The paper analyzes exerkine responsiveness in exercised rodents using multi-omics data to identify tissue-specific and sex-dimorphic responses.

This study shows that enhancing the muscle-to-brain axis in Alzheimer's disease mice reduces amyloid plaques and improves cognitive function through neurotrophic and synaptic signaling.

The paper validates an ELISA method for measuring fecal glucocorticoid metabolites in yellow-bellied marmots, finding it more reliable and sustainable than a previous radioimmunoassay.

SPiRiT uses explainable deep learning to predict spatial single-cell gene expression from histological images, improving accuracy over existing methods.

The paper identifies driver genes for type 2 diabetes using causal network perturbation analysis and single-cell RNA sequencing in mouse models.