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Application of machine learning approaches for design of more selective herbicides


Pehar, Vesna; Oršolić, Davor; Jadrijević-Mladar Takač, Milena; Stepanić, Višnja
Application of machine learning approaches for design of more selective herbicides // Book of Abstracts, The 3rd COST-sponsored ARBRE- MOBIEU plenary meeting / Ivošević DeNardis, Nadica ; Campos-Olivas, Ramon ; Miele, Adriana E. ; England, Patrick ; Vuletić, Tomislav (ur.).
Zagreb: Ruđer Bošković Institute and Croatian Biophysical Society, 2019. str. 113-114 (poster, međunarodna recenzija, sažetak, znanstveni)


Naslov
Application of machine learning approaches for design of more selective herbicides

Autori
Pehar, Vesna ; Oršolić, Davor ; Jadrijević-Mladar Takač, Milena ; Stepanić, Višnja

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

Izvornik
Book of Abstracts, The 3rd COST-sponsored ARBRE- MOBIEU plenary meeting / Ivošević DeNardis, Nadica ; Campos-Olivas, Ramon ; Miele, Adriana E. ; England, Patrick ; Vuletić, Tomislav - Zagreb : Ruđer Bošković Institute and Croatian Biophysical Society, 2019, 113-114

ISBN
978-953-7941-28-4

Skup
The 3rd COST-sponsored ARBRE-MOBIEU plenary meeting

Mjesto i datum
Zagreb, Craotia, 18-20.03.2019

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Herbicides, machine learning methods, models, QSAR

Sažetak
Herbicides are chemical molecules used for destruction of weeds. Massive usage of herbicides has resulted in two global problems: increase in herbicide resistance and harmful impact of human health [1, 2]. In order to facilitate development of novel, more specific herbicides and development of strategies for impeding the weed resistance development, we have carried out extensive in silico analysis of the set of herbicides. Herein, we present results revealing links between structural, physicochemical, ADME (Absorption, Distribution, Metabolism, Excretion) and toxic features for herbicides. The analysis has been done by using proper machine learning approaches. References [1] Forouzesh A, Zand E, Soufizadeh S, Foroushani SS. W Classification of herbicides according to chemical family for weed resistance management strategies–an update, Weed Res, 2015 ; 55: 334-358. doi: 10.1111/wre.12153. [2] Lushchak VI, Matviishyn TM, Husak VV, Storey JM, Storey KB. Pesticide toxicity: a mechanistic approach. EXCLI J. 2018 ; 17:1101-1136. doi: 10.17179/excli2018-1710.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Interdisciplinarne prirodne znanosti, Biotehnologija



POVEZANOST RADA


Projekt / tema
KK.01.1.1.01

Ustanove
Farmaceutsko-biokemijski fakultet, Zagreb,
Institut "Ruđer Bošković", Zagreb