Naslov
(Re)purposing starts virtually by predictive machine-learning models

Autori
Stepanić, Višnja ; Oršolić, Davor ; Šmuc, Tomislav

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
27th Croatian Meeting of Chemists and Chemical Engineers and 5th Symposium Vladimir Prelog : Book of Abstracts / Marković, Dean ; Meštrović, Ernest ; Namjesnik, Danijel ; Tomašić, Vesna - Zagreb : Hrvatsko kemijsko društvo, 2021, 16-16

Skup
27. hrvatski skup kemičara i kemijskih inženjera (27HSKIKI)

Mjesto i datum
Veli Lošinj, Hrvatska, 05.10.2021. - 08.10.2021

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Recenziran

Ključne riječi
Cheminformatics, Herbicides, Kinases, Machine learning

Sažetak
The cheapest, fastest and efficient way to find active compounds for biological targets, novel biological activities for compounds “in shelves” or to reveal targets for discovered natural products, is to test compounds virtually by using proper in silico approaches and/or models at the beginning. The predictive machine learning (ML) model developed for specific (bio)activity can be applied for prioritizing assays for in vitro testing of compounds and their (re)purposing. The two ML models which may shed light on potential biological activities for compounds, will be presented. They have been developed by using publicly available datasets and are incorporated within virtual modular platforms for detecting potential phytotoxic molecules and kinase inhibitors.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Biologija, Poljoprivreda (agronomija), Interdisciplinarne biotehničke znanosti

POVEZANOST RADA