Computer Based Drug Design and Machine Learning for the Computational Search of Novel Carbohydrate Binding Protein Inhibitors.
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Pieters, Roland | |
| dc.contributor.author | Markink, Job | |
| dc.date.accessioned | 2024-10-31T01:02:11Z | |
| dc.date.available | 2024-10-31T01:02:11Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/48047 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | Computer-Aided Drug Design (CADD) and Machine Learning (ML) are two fields that are constantly developing and are starting to become an important part of drug discovery. This review will focus on Structure-Based Drug Design and Ligand-Based Drug Design virtual screenings as techniques for CADD and looks at how ML can be incorporated in the drug discovery process. In addition, limitations of these fields and their future opportunities will be discussed. | |
| dc.title | Computer Based Drug Design and Machine Learning for the Computational Search of Novel Carbohydrate Binding Protein Inhibitors. | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Drug Innovation | |
| dc.thesis.id | 40664 |
