Please use this identifier to cite or link to this item:
https://biore.bio.bg.ac.rs/handle/123456789/4842| Title: | Combining machine learning and non-linear dynamics modeling to understand COVID-19 risk factors | Authors: | Đorđević, Marko Salom, I. Djordjevic, M. Marković, Sofija Rodić, Anđela Milicevic, M. Tumbas Z. Marko Zigic, D. |
Issue Date: | 4-Jul-2022 | Rank: | M34 | Publisher: | Federal Res. Center - Inst. of Cytology and Genetics SB RAS | Citation: | Djordjevic M, Salom I, Djordjevic M, Sofija M, Rodic A, Milicevic M, Tumbas M, Zigic D. (2022) Combining machine learning and non-linear dynamics modeling to understand COVID-19 risk factors. 13th International Multiconference on Bioinformatics of Genome Regulation and Structure/Systems Biology - BGRS/SB, 04-08 July 2022, Novosibirsk, Russia, Book of abstracts (pp.897-898), Published by: Federal Res. Center - Inst. of Cytology and Genetics SB RAS. | Start page: | 897 | End page: | 898 | Conference: | 13th Internationa Multiconference on Bioinformatics of Genome Regulation and Structure/Systems Biology | Description: | Book of abstracts (pp.897-898) |
URI: | https://biore.bio.bg.ac.rs/handle/123456789/4842 |
| Appears in Collections: | Conference abstract |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.