Within the vast world of biology lies an infinite spectrum of entities, of which genes, drugs, proteins, 
microbes are some of the examples. How these entities interact with each other is an important question 
which can be addressed by graph theory in the field of network biology comparing how these. Relationships, 
or biological networks, change across different states. Like the state of health and disease is a 
pertinent question, but is challenged by the sheer plurality and the size of the networks. Comparing and 
visualizing the interaction profiles is therefore challenging, and we came up with a simple proposition 
using the classical Venn diagram to not only identify but also visualize what's common and what's not. 
Between the multiple biological networks, we proposed net sets, an idea of integrating network and Venn 
diagrams and demonstrated it using simple JavaScript based application that got published in Oxford 
University Press Bioinformatic Journal as net assets. JS applications of such a network comparison can 
actually go beyond biology. Social science could use it for behavioral studies, economics could use it. 
For product trade structures, Transportation for example, could use it for successful flight network 
analysis. Basically, wherever there is a network comparison intended, net sets could be useful.