Network-based methods for the elucidation of disease and drug mechanisms
Abstract/Contents
- Abstract
- Complex, chronic diseases represent some of the most common diseases known to man, yet often little is understood regarding the underlying biological mechanisms, leading to challenges in their prevention and treatment. Characterizing complex disease can be daunting, as combinations of perturbations in a delicate web of genetic and environmental interactions may lead to a similar disease phenotype. These intricacies provide an opportunity for computational approaches, in particular network-based approaches, which have the ability to capture and model large, complex biological systems. I have leveraged the power and versatility of these approaches and developed novel network-based methods for phenotype classification and drug discovery. I applied my methods to inflammatory bowel disease (IBD), a chronic, heterogeneous disease which has significant unmet need in subtyping patients, predicting treatment response, and optimizing treatment regimens. I first discovered new candidate genes implicated in IBD by traversing a network consisting of IBD related genes and Mendelian phenotypes. Next, I developed a new supervised, individualized pathway-based classification method, and demonstrated its superiority over existing gene-based and pathway-based methods for distinguishing the two common subtypes of IBD. I showed that pathway-based methods can extract robust features for disease differentiation as well as provide mechanistic biological insight into disease subtypes. Finally, I developed a network-based method for drug repurposing which predicts personalized drug treatments for individual patients. Through these works, I demonstrate the potential of network-based bioinformatics tools in furthering patient care by advancing our understanding of disease and drug mechanisms
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Han, Lichy |
|---|---|
| Degree supervisor | Altman, Russ |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Hastie, Trevor |
| Thesis advisor | Khatri, Purvesh |
| Degree committee member | Hastie, Trevor |
| Degree committee member | Khatri, Purvesh |
| Associated with | Stanford University, Department of Biomedical Informatics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Lichy Han |
|---|---|
| Note | Submitted to the Department of Biomedical Informatics |
| Thesis | Thesis Ph.D. Stanford University 2019 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Lichy Han
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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