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Svetlana Kutuzova
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Year
Cameo: a Python library for computer aided metabolic engineering and optimization of cell factories
JGR Cardoso, K Jensen, C Lieven, AS Lærke Hansen, S Galkina, ...
ACS synthetic biology 7 (4), 1163-1166, 2018
662018
Machine learning and deep learning applications in microbiome research
R Hernández Medina, S Kutuzova, KN Nielsen, J Johansen, LH Hansen, ...
ISME Communications 2 (1), 98, 2022
632022
SmartPeak automates targeted and quantitative metabolomics data processing
S Kutuzova, P Colaianni, H Rost, T Sachsenberg, O Alka, O Kohlbacher, ...
Analytical chemistry 92 (24), 15968-15974, 2020
232020
Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
S Kutuzova, O Krause, D McCloskey, M Nielsen, C Igel
arXiv preprint arXiv:2101.07240, 2021
142021
Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes
N Al-Sari, S Kutuzova, T Suvitaival, P Henriksen, F Pociot, P Rossing, ...
EBioMedicine 80, 2022
72022
Adversarial and variational autoencoders improve metagenomic binning
PP Líndez, J Johansen, S Kutuzova, AI Sigurdsson, JN Nissen, ...
Communications Biology 6 (1), 1073, 2023
32023
Bi-modal variational autoencoders for metabolite identification using tandem mass spectrometry
S Kutuzova, C Igel, M Nielsen, D McCloskey
bioRxiv, 2021.08. 03.454944, 2021
32021
Использование методов машинного обучения для построения оптимального портфеля ценных бумаг
СА Галкина
International Journal of Open Information Technologies 2 (6), 14-20, 2014
22014
OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data
J Pfeuffer, C Bielow, S Wein, K Jeong, E Netz, A Walter, O Alka, L Nilse, ...
Nature Methods, 1-3, 2024
12024
OpenMS 3 expands the frontiers of open-source computational mass spectrometry
T Sachsenberg, J Pfeuffer, C Bielow, S Wein, K Jeong, E Netz, A Walter, ...
2023
Taxometer: Improving taxonomic classification of metagenomics contigs
S Kutuzova, M Nielsen, P Piera Lindez, J Nybo Nissen, S Rasmussen
bioRxiv, 2023.11. 23.568413, 2023
2023
Machine learning methods for metabolomics data analysis
S Kutuzova
2022
DD-DeCaF: Data-Driven Design of Cell Factories and Communities
ME Beber, D Dannaher, M Fodor, S Galkina, NH Redestig, ...
DTU Sustain 2017, R-3, 2017
2017
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