Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Using machine learning to understand the link between gene essentiality, gene expression and the chemosensitivity of cancer cells
The emergence of pharmacogenomics databases has presented unique opportunities to leverage machine learning in precision medicine, particularly in drug response prediction. In this thesis, an in-depth investigation is conducted on carefully curated and integrated breast cancer focused datasets from...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English English |
| Published: |
Department of Integrative Biomedical Sciences (IBMS)
2025
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: Using machine learning to understand the link between gene essentiality, gene expression and the chemosensitivity of cancer cells
- Retracted: Screening Tumor-Related Genes of Gallbladder Cancer Based on AR-Based Tumor Expression Profile Gene Chip
- Probing the Mycobacterial Cell Envelope: CRISPR interference-mediated investigation of two essential genes in the galactan biosynthetic pathway
- Deep Learning for Multi-Tissue Cancer Classification of Gene Expressions
- The structure and expression of the sheep elastin gene
- Collagen gene expression in human cancer
- Differentially expressed genes in oesophageal cancer