  Disease occurs due to aberrant expression of genes and modulation of the
biological pathways along which they lie. Inference of activated gene pathways,
using gene expression data during disease progression, is an important problem.
In this work, we have developed a generalizable framework for the
identification of interacting pathways while incorporating biological realism,
using functional data analysis and manifold embedding techniques. Additionally,
we have also developed a new method to query for the differential co-ordinated
activity of any desired pathway during disease progression. The methods
developed in this work can be generalized to any conditions of interest.
