20.500.12556/RUL-127776 Guided extraction of genome-scale metabolic models for the integration and analysis of omics data Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT an tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value <0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the variability (>90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context. genome-scale metabolic model model extraction methods context-specific metabolic model omics data integration subsystem enrichment analysis model interpretability metabolni modeli na nivoju genoma ekstrakcija modelov kontekstno specifični metabolni modeli integracija omskih podatkov analiza obogatitve metabolnih podsistemov true false true Angleški jezik Slovenski jezik Članek v reviji 2021-06-22 19:11:00 2021-06-22 19:11:03 2022-09-06 03:53:04 0000-00-00 00:00:00 2021 0 0 Str. 3521-3530 Vol. 19 2021 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:575.112 2001-0370 10.1016/j.csbj.2021.06.009 66227971 RAZ_Walakira_Andrew_2021.pdf RAZ_Walakira_Andrew_2021.pdf 1 387CBB2ECEF0F7D3B62A374823E340FD f55e4d5f7ea20d7b4099aa6d6d7bd4649fb6930418847d92fcb4e5a10e3bc770 eca80ce6-d37f-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=144307 https://www.sciencedirect.com/science/article/pii/S2001037021002476 1 b748e968-d37c-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=144306 Medicinska fakulteta Fakulteta za računalništvo in informatiko 0 0 0