Gregory R. Smith

In 174 sedentary adults, resistance exercise changed more muscle molecular features than endurance exercise across omes and time points; network analysis nominates MEF2A and NFIC as regulatory hubs.

The paper presents initial findings from the MoTrPAC consortium, showing that acute and chronic exercise induce distinct physiological and molecular responses, with chronic training improving key health metrics.

The paper analyzes multi-omic, multi-tissue molecular responses to acute exercise in sedentary adults, identifying key pathways and exerkines involved in exercise effects.

The paper identifies shared and distinct biochemical responses to different exercise modes through plasma proteomics, metabolomics, and transcriptomics in sedentary humans.

The paper uses single-nucleus multiomics to study pituitary cell changes during the mouse estrous cycle, finding stage-dependent gene regulatory circuits and validated ETS2-driven gene expression patterns.

This study identifies tissue-specific lncRNA responses to endurance exercise in rats, revealing sex differences and potential therapeutic implications.

The paper identifies tissue-specific transcriptional regulatory programs in rats undergoing endurance exercise training by integrating chromatin accessibility, DNA methylation, and gene expression data.

The paper profiles multi-omic changes in abdominal subcutaneous adipose tissue after acute exercise in sedentary adults, identifying distinct molecular programs and candidate exerkines.

This study examines how acute endurance and resistance exercise alter alternative splicing in human skeletal muscle, adipose tissue, and blood, identifying 5102 differential splicing events and their regulatory mechanisms.

The paper creates a large-scale Consensus Pituitary Atlas to improve reproducibility and enable marker discovery and analysis in pituitary research.

The paper uses single-nucleus multiome sequencing to analyze gene regulatory changes in human skeletal muscle after endurance exercise, identifying fiber-type specific regulatory programs and transcription factor networks.

This study examines how endurance exercise training affects rat subcutaneous white adipose tissue, revealing sex-specific molecular responses and differences in adiposity and metabolism.

This paper introduces DL-MRA, a method to infer network structures from perturbation time course data, showing it can robustly identify small networks but has limitations for signaling networks.

This study profiles multi-omic changes in multiple tissues of rats during endurance exercise training, identifying molecular adaptations and sex-specific responses across time.

The paper uses single-cell imaging and machine learning to predict cell division from ERK and Akt activity dynamics in MCF10A cells, finding ERK alone predicts division with AUC=0.74.