Using network inference to discover molecular pathways underlying cytokine synergism and age-related neurodegeneration

New high-throughput "omic" methods can help shed light on molecular pathways underpinning diseases ranging from cancers to neurodegenerative disorders. However, effectively integrating information across these diverse data types is challenging. Network modeling approaches can help bridge this gap. In particular, the Prize- Collecting Steiner Forest approach (PCSF) is a network modeling method that provides high-confidence subnetworks of physically interacting molecules by integrating diverse "omics" data with prior knowledge from protein-protein interaction networks (PPIs). However, PCSF is sensitive to initial parameterization and generating biological hypotheses from the resulting subnetworks can often be difficult. This study increases the interpretability of subnetwork solutions generated PCSF by studying the effect of varying PCSF free parameters and adding annotations for subcellular localization. The PCSF approach is then used to elucidate pathways underlying synergy between cytokines, pro-inflammatory molecules that mediate diverse biological phenomena ranging from anti-viral immunity to autoimmune disorders like inflammatory bowel disease (IBD). In addition, PCSF approach is applied in a cross-species context to integrate information from Drosophila models for neurodegeneration and human Alzheimer's Disease (AD) patients to investigate proximal conserved mechanisms of age-related neurodegeneration.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Hwang, Bryce

Advisor dc:contributor.advisor

• Ernest Fraenkel.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/119757

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/119757