Augmenting drug mechanism prediction with text mining
Abstract/Contents
- Abstract
- The biomedical literature is the most comprehensive resource for known information and, more specifically, high quality low-throughput data. While expertly curated databases aim to annotate domain-specific biomedical relationships, large-scale curation efforts become infeasible as the biomedical literature grows exponentially. Due to the availability of high-throughput experimental data, many computational methods for drug discovery and repurposing have focused on incorporating this data into their algorithms; however, data extracted from the literature is equally valuable. To assess the impact of literature-extracted biomedical relationships on drug mechanism prediction, I extracted gene-gene, gene-drug, and gene-disease from full text literature articles using the system DeepDive. In addition, I developed Snorkel applications to extract bacteria-gut and chemical reaction relationships from abstracts. To integrate literature and abstract-derived biomedical relationships for augmenting computational approaches for drug mechanism prediction, I focused on two applications: detecting semantic network motifs for drug target prediction and predicting drug metabolism in the human gut microbiome.
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 | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Mallory, Emily K |
|---|---|
| Degree supervisor | Altman, Russ |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Khatri, Purvesh |
| Thesis advisor | Ré, Christopher |
| Degree committee member | Khatri, Purvesh |
| Degree committee member | Ré, Christopher |
| Associated with | Stanford University, Program in Biomedical Informatics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Emily K. Mallory. |
|---|---|
| Note | Submitted to the Program in Biomedical Informatics. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Emily Kathryn Mallory
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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