Rajamani, D.S.K. Gene Expression Network Analysis (GENA) – A Biostatistical Method to Unravel Intricate Relationships Between Genes. Preprints2023, 2023120377. https://doi.org/10.20944/preprints202312.0377.v1
APA Style
Rajamani, D.S.K. (2023). Gene Expression Network Analysis (GENA) – A Biostatistical Method to Unravel Intricate Relationships Between Genes. Preprints. https://doi.org/10.20944/preprints202312.0377.v1
Chicago/Turabian Style
Rajamani, D.S.K. 2023 "Gene Expression Network Analysis (GENA) – A Biostatistical Method to Unravel Intricate Relationships Between Genes" Preprints. https://doi.org/10.20944/preprints202312.0377.v1
Abstract
Deeper understanding of biological processes, disease mechanisms, and prospective therapeutic targets can be attained by Gene Expression Network Analysis (GENA), which offers a potent framework for revealing the intricate regulatory mechanisms controlling gene expression. GENA is a computational method used to understand the intricate interactions and relationships between the genes in a biological system. It entails using network theory, statistical analysis, and gene expression data to pinpoint functional modules, regulatory linkages, and important genes or pathways involved in a particular biological process or illness. This chapter broadly outlines the principles and practice of GENA, to an novice reader and outlines a simple method of performing a GENA using online Rice gene expression datasets available in various websites.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
