Discovering molecular mechanisms of human disease through gene sets and networks
Abstract
Molecular processes play a key role in the development of disease.
Yet, there is still not enough known about molecular causes of
disease. In this thesis, we introduce methods to discover hidden
connections between biological functions and disease using gene sets
and networks.
We first investigate a topological property of pathways in
protein-protein interaction networks. We find mediating pathways for
three pulmonary diseases using a new measurement called pathway
centrality which measures the amount of information flow between
disease genes and differentially expressed genes handled by a pathway.
Second, we identify connections between developmental processes and
disease by statistically testing overlaps between developmental gene
sets and disease gene sets. We handle missing disease-gene association
information by pooling disease genes from specific disease terms to
more general disease terms in a disease taxonomy. While successful,
this work highlights a need for more molecular disease taxonomies to
improve the efficacy of gene pooling. We therefore performed a pilot
study to infer disease hierarchies only using disease-gene association
information.
In this talk, I will talk about our methods that highlight novel
connections between gene sets and disease, and our findings that may
lead to development of new therapeutic solutions.