మా గ్రూప్ ప్రతి సంవత్సరం USA, యూరప్ & ఆసియా అంతటా 3000+ గ్లోబల్ కాన్ఫరెన్స్ ఈవెంట్లను నిర్వహిస్తుంది మరియు 1000 కంటే ఎక్కువ సైంటిఫిక్ సొసైటీల మద్దతుతో 700+ ఓపెన్ యాక్సెస్ జర్నల్లను ప్రచురిస్తుంది , ఇందులో 50000 మంది ప్రముఖ వ్యక్తులు, ప్రఖ్యాత శాస్త్రవేత్తలు ఎడిటోరియల్ బోర్డ్ సభ్యులుగా ఉన్నారు.
ఎక్కువ మంది పాఠకులు మరియు అనులేఖనాలను పొందే ఓపెన్ యాక్సెస్ జర్నల్స్
700 జర్నల్స్ మరియు 15,000,000 రీడర్లు ప్రతి జర్నల్ 25,000+ రీడర్లను పొందుతున్నారు
Brown T
Understanding the intricate interplay between gene expression regulation and cellular metabolism is fundamental to unraveling the complexities of living organisms. This review provides a comprehensive overview of the dynamic relationship between gene expression and metabolic processes, exploring the bidirectional influence each exerts on the other. The first section delves into the regulatory mechanisms governing gene expression, ranging from transcriptional and post-transcriptional controls to epigenetic modifications. Special emphasis is placed on recent advancements in technologies like CRISPR/Cas9, single-cell RNA sequencing, and chromatin conformation capture, which have revolutionized our ability to dissect and manipulate gene regulatory networks. The subsequent segment focuses on the central role of metabolism in shaping cellular functions. Metabolic pathways, including glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation, are discussed in the context of their impact on energy production, biosynthesis, and cellular signaling. Metabolism's adaptability to environmental cues and its integration with cellular pathways highlight its crucial role in maintaining cellular homeostasis. The third section examines the reciprocal relationship between gene expression and metabolism. Here, we explore how metabolic signals influence gene regulatory networks and, conversely, how gene expression modulates metabolic pathways. Examples from diverse biological systems, including development, immune response, and cancer, underscore the complexity and versatility of these interactions. In the final part, we discuss emerging trends and future directions in the field. Integration of multi-omics data, systems biology approaches, and the advent of artificial intelligence in analyzing large-scale datasets promise to deepen our understanding of the gene expression-metabolism nexus. Furthermore, implications for therapeutic interventions in diseases characterized by dysregulated gene expression and metabolism are considered.