Text-Enhanced Relational Learning for Drug Repurposing – Bc. Marek Toma
Bc. Marek Toma
Master's thesis
Text-Enhanced Relational Learning for Drug Repurposing
Text-Enhanced Relational Learning for Drug Repurposing
Abstract:
"Drug repurposing" je stratégia pre hľadanie nových terapeutických využití pre existujúce lieky. Výpočtové prístupy založené na strojovom učení môžu pomôcť so znížením ceny a zrýchlením vývoja liekov. V tejto práci sme vyvinuli model založený na relačnom učení pre predikciu asociácií medzi liekmi a chorobami. Ako prvé sme vytvorili model natrénovaný na biomedicínskom znalostnom grafe. Ako dalšie sme …moreAbstract:
Drug repurposing is a strategy for the development of new treatment options with already existing drugs. Computational approaches based on machine learning can further reduce the cost and accelerate the drug development process. In this work, we develop relational learning models for the prediction of associations between drugs and diseases. First, we design a model trained on the biomedical knowledge …more
Language used: English
Date on which the thesis was submitted / produced: 15. 12. 2023
Identifier:
https://is.muni.cz/th/g5y1k/
Thesis defence
- Date of defence: 13. 2. 2024
- Supervisor: doc. Mgr. Bc. Vít Nováček, PhD
- Reader: Mgr. Petr Zelina
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Artificial intelligence and data processing / Machine learning and artificial intelligence