Machine learning for small molecule lead optimization
Abstract/Contents
- Abstract
- The development of small molecule drugs is a lengthy and expensive process that could potentially be improved by new technologies. Lead optimization is an important part of small molecule drug discovery, where initial hit molecules are gradually developed into suitable drug candidates. It can be described as an iterative cycle of design, make and test phases, which can be further broken down into a series of concrete sub-problems, namely: molecular property prediction, molecule generation, chemical synthesis planning, experimental chemical synthesis, and experimental testing. This thesis explores machine learning methods to tackle a few of the sub-problems in small molecule lead optimization, with a focus on the early design phases
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 | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Liu, Bowen |
|---|---|
| Degree supervisor | Leskovec, Jurij |
| Thesis advisor | Leskovec, Jurij |
| Thesis advisor | Kim, Peter, 1974- |
| Thesis advisor | Pande, Vijay |
| Thesis advisor | Wender, Paul A |
| Degree committee member | Kim, Peter, 1974- |
| Degree committee member | Pande, Vijay |
| Degree committee member | Wender, Paul A |
| Associated with | Stanford University, Department of Chemistry |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Bowen Liu |
|---|---|
| Note | Submitted to the Department of Chemistry |
| Thesis | Thesis Ph.D. Stanford University 2020 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Bowen Liu
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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