STATISTICAL MODELLING OF GENE REGULATORY NETWORKS

Abstract

Biological network analysis is a rapidly growing field which is increasing our understanding of biological process. The study and modeling of biological networks are important in life science today. A wide range of scientists are interested in quantifying the link between nodes in a system, however the linkage is not as straight forward as it might seem. The challenge is, how to extract relevant information and translate this information to knowledge that can yield clinically actionable results. Insights gained from successful computational statistics of networks topology can, in principle, be used to design new experiments that test these insights in a broad context. In this work, a newly derived discretised Power probability density function is proposed for in-degree distribution of gene regulatory networks.  A statistical comparison of the newly proposed degree distribution was made with alternative degree distribution in literature.