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Model verification tools: a computational framework for verification assessment of mechanistic agent-based models., , , и . BMC Bioinform., 22-S (14): 626 (2021)A multi-step and multi-scale bioinformatic approach to investigate potential source of cross-reactive immunity against SARS-CoV-2 UK variant., , , , , и . BIBM, стр. 3303-3307. IEEE, (2021)A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets., , , , , и . Briefings Bioinform., (2022)In Silico Evaluation of Daclizumab and Vitamin D Effects in Multiple Sclerosis Using Agent Based Models., , , , и . CIBB, том 12313 из Lecture Notes in Computer Science, стр. 285-298. Springer, (2019)Agent based modeling of relapsing multiple sclerosis: a possible approach to predict treatment outcome., , , , , , , и . BIBM, стр. 1380-1385. IEEE Computer Society, (2018)PEAK: A Clever Python Tool for Exploratory, Regression, and Classification Data. A Case Study for COVID-19., , , , и . BIOMESIP, том 12940 из Lecture Notes in Computer Science, стр. 361-370. Springer, (2021)Verify: a toolbox for deterministic verification of computational models., , , , , , и . BIBM, стр. 1262-1267. IEEE, (2020)An agent based modeling approach for the analysis of tuberculosis - immune system dynamics., , , , , , и . BIBM, стр. 1386-1392. IEEE Computer Society, (2018)Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB., , , , , , , , , и 1 other автор(ы). BMC Bioinform., 21-S (17): 458 (2020)Evaluation of the predictive capability of PETAL tool: a retrospective study on potential tyrosine kinases drug resistance targets., , , , и . BIBM, стр. 1275-1280. IEEE, (2020)