Journal of sport and health science · 2025
ExerGeneDB: A physical exercise-regulated differential gene expression database.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Pan Ling, Ai Songwei, Shi Xiaohui, Tong Xiaolan, Spanos Michail, Li Guoping, Cretoiu Dragos, Gao Juan, Zhou Qiulian, Xiao Junjie
Аннотация
BACKGROUND: Exercise induces molecular changes that involve multiple organs and tissues. Moreover, these changes are modulated by various exercise parameters-such as intensity, frequency, mode, and duration-as well as by clinical features like gender, age, and body mass index (BMI), each eliciting distinct biological effects. To assist exercise researchers in understanding these changes from a comprehensive perspective that includes multiple organs, diverse exercise regimens, and a range of clinical features, we developed Exercise Regulated Genes Database (ExerGeneDB), a database of exercise-regulated differential genes.
METHODS: ExerGeneDB aggregated publicly available exercise-related sequencing datasets and subjected them to uniform quality control and preprocessing. The data, encompassing a variety of types, were organized into a specialized database of exercise-regulated genes. Notably, ExerGeneDB conducted differential analyses on this collected data, leveraging curated clinical information and accounting for important factors such as gender, age, and BMI.
RESULTS: ExerGeneDB has assembled 1692 samples from rats and mice as well as 4492 human samples. It contains data from various tissues and organs, such as skeletal muscle, blood, adipose tissue, intestine, heart, liver, spleen, lungs, kidneys, brain, spinal cord, bone marrow, and bones. ExerGeneDB features bulk ribonucleic acid sequencing (RNA-seq) (including non-coding RNA (ncRNA) and protein-coding RNA), microarray (including ncRNA and protein-coding RNA), and single cell RNA-seq data.
CONCLUSION: ExerGeneDB compiles and re-analyzes exercise-related data with a focus on clinical information. This has culminated in the creation of an interactive database for exercise regulation genes. The website for ExerGeneDB can be found at: https://exergenedb.com.
METHODS: ExerGeneDB aggregated publicly available exercise-related sequencing datasets and subjected them to uniform quality control and preprocessing. The data, encompassing a variety of types, were organized into a specialized database of exercise-regulated genes. Notably, ExerGeneDB conducted differential analyses on this collected data, leveraging curated clinical information and accounting for important factors such as gender, age, and BMI.
RESULTS: ExerGeneDB has assembled 1692 samples from rats and mice as well as 4492 human samples. It contains data from various tissues and organs, such as skeletal muscle, blood, adipose tissue, intestine, heart, liver, spleen, lungs, kidneys, brain, spinal cord, bone marrow, and bones. ExerGeneDB features bulk ribonucleic acid sequencing (RNA-seq) (including non-coding RNA (ncRNA) and protein-coding RNA), microarray (including ncRNA and protein-coding RNA), and single cell RNA-seq data.
CONCLUSION: ExerGeneDB compiles and re-analyzes exercise-related data with a focus on clinical information. This has culminated in the creation of an interactive database for exercise regulation genes. The website for ExerGeneDB can be found at: https://exergenedb.com.