A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

• Published in: International journal of molecular sciences Vol. 25; no. 8; p. 4224
• Main Authors: Pepe, Gerardo, Appierdo, Romina, Ausiello, Gabriele, Helmer-Citterich, Manuela, Gherardini, Pier Federico
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.04.2024
• Subjects: Algorithms; Atherosclerosis; Breast cancer; Cardiomyopathy; Cardiovascular disease; Cardiovascular Diseases - genetics; Cardiovascular Diseases - metabolism; Circulatory system; Cohort analysis; Datasets; Development and progression; DNA binding proteins; Extracellular matrix; Fatty acids; Gene expression; Gene Expression Regulation; gene regulatory network; Gene Regulatory Networks; Genes; Genetic transcription; Heart failure; Heart Failure - genetics; Heart Failure - metabolism; Humans; Hypertension; Ischemia; Medical research; Medicine, Experimental; Metabolism; MicroRNAs; Pathology; Physiological aspects; Proteins; Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; Tumors; cardiomyopathy; cardiovascular disease; gene regulatory network

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopa...