Methods for classifying samples based on network modularity

A method for generating a network signature identifying a biological state, a disease or disease stage, comprising:

• (a) obtaining gene expression levels from a reference population having two different biological states, diseases or disease stages;
• (b) dividing said reference population gene expression levels into two groups, each group characteristic of one said different biological state, disease or disease stage;
• and
• (c) assessing differences in relative gene expression levels between a hub protein and an interacting partner in said groups to identify a hub protein whose expression relative to an interacting partner is characteristic of one said biological state, disease or disease stage.

A system comprising a computer processor capable of processing gene expression data for a hub protein and its interacting partners, an input device, an output device, and a memory capable of storing computer-readable instructions, wherein the contents of the memory comprises computer-readable instructions that if executed are capable of directing the computer to:

• (a) receive gene expression level data from a biological sample from a subject;
• (b) determine the relative expression of a hub protein and an interacting partner in said sample;
• (c) compare the relative expression to a standard or model;
• and
• (d) output an indication of the presence of a biological state, a disease or disease stage, likelihood thereof, or prognosis therefor.