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Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach
| Title: | Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach | Authors: | Pawellek, Ruben; Krmar, Jovana   ; Leistner, Adrian; Đajić, Nevena ; Otašević, Biljana ; Protić, Ana ; Holzgrabe, Ulrike |
Issue Date: | 2021 | Publication: | Journal of Cheminformatics | ISSN: | 1758-2946 Journal of Cheminformatics Search Idenfier |
Publisher: | BioMed Central Ltd | Type: | Article | Collation: | vol. 13 br. 1 | DOI: | 10.1186/s13321-021-00532-0 | WoS-ID: | 000673977300001 | Scopus-ID: | 2-s2.0-85110487489 | PMID: | 34266497 | PMCID: | PMC8281619 | URI: | https://farfar.pharmacy.bg.ac.rs/handle/123456789/3926 https://enauka.gov.rs/handle/123456789/129304 |
Project: | DAAD PPP Program for Project-Related Personal Exchange with Serbia Fund of the University of Wuerzburg Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije, Ugovor br. 200161 (Univerzitet u Beogradu, Farmaceutski fakultet) (RS-200161) |
M-category: | 21aM21a |
