Identification and Query of Activated Gene Pathways in Disease Progression

TL;DR

This paper introduces a framework for identifying and querying activated gene pathways during disease progression using functional data analysis and manifold embedding, enabling better understanding of gene interactions in diseases.

Contribution

The work presents a novel, generalizable approach for identifying interacting pathways and querying their activity changes during disease progression, incorporating biological realism.

Findings

Framework successfully identifies activated pathways in disease data

Method enables querying differential pathway activity during progression

Approach is applicable to various conditions and datasets

Abstract

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.