Investigating the Systems Biology in the Context of Big Data, Statistics and Networks

From the beginning of the present millennium, science is going through two rapidly changing
phenomena: one is that the capabilities of the computers and software tools are increasing from
terabytes to petabytes and beyond and the other is the advancement in molecular biological
experiments producing piles of data related to genome and RNA sequence, protein and metabolite
abundance, protein-protein interaction, gene expression and so on. As a natural consequence these
two fields have become complementary to each other bridged by other branches of science e.g.
statistics, mathematics, physics, chemistry etc. Thus the combination of versatile knowledge caused
the advent of big data biology, network biology and many other new subjects. Network biology
facilitates the system-level understanding of the cell or cellular components and sub-processes. Thus
advanced biology has recently become a data intensive science and this rather new branch of biology
is referred to as systems biology. The purpose of systems biology is to understand organisms or cells
as a whole at various levels of functions and mechanisms. However, along the way to achieve that
goal many other practical applications will be invented and introduced e.g. development of new
generation medical tests, drugs, foods, fuel, materials, sensors etc. Systems biology is now facing the
challenges of analyzing big molecular biological data and huge biological networks. This book chapter
will focus on some aspects of Systems Biology in the Context of Big Data, Statistics and Networks.