Инд. авторы:	Senotrusova S.D., Voropaeva O.F.
Заглавие:	Numerical analysis of the diagnostic properties of tumor markers
Библ. ссылка:	Senotrusova S.D., Voropaeva O.F. Numerical analysis of the diagnostic properties of tumor markers // Systems Biology and Bioinformatics: The Ninth International Young Scientists School SBB-2017. Abstracts / Compilers: О. Petrovskaya, Y. Orlov, S. Zubova. - 2017. - Новосибирск: Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук. - P.61-62. - ISBN: 978-5-91291-031-9.
Внешние системы:	РИНЦ: 30045647;
Ключевые слова:	numerical simulation; delay differential equations; miRNA; p53; tumor marker;
Издано:	2017
Физ. характеристика:	с.61-62
Конференция:	Название: Ninth International Young Scientists School "Systems Biology and Bioinformatics" Аббревиатура: SBB-2017 Город: Yalta Страна: Russia Даты проведения: 2017-06-25 - 2017-06-30
Цитирование:	1. 1. Lane D., Levine A. (2010) p53 research: The past thirty years and the next thirty years. Cold Spring Harb. Perspect. Biol. 2:a000893. 2. 2. Loewer A., Batchelor E., Gaglia G., Lahav G. (2010). Basal dynamics of p53 reveals transcriptionally attenuated pulses in cycling cells. Cell. 142(1):89-100. 3. 3. Batchelor E., Loewer A., Mock C., Lahav G. (2011). Stimulus-dependent dynamics of p53 in single cells. Molecular Systems Biology. 7(488):8. 4. 4. Hermeking H. (2012). MicroRNAs in the p53 network: micromanagement of tumor suppression, Nature reviews cancer. 12(9):613-626. doi: 10.1038/nrc3318. 5. 5. Voropaeva O.F., Kozlova A.O., Senotrusova S.D. (2016) Passage from delay equation to ODE system in the mathematical model of the tumor markers network. Computational Technologies. 21(2):12-25. 6. 6. Voropaeva O.F., Senotrusova S.D., Shokin Yu.I. (2017). Deregulation of p53-dependent microRNAs: the results of mathematical modeling. Mathematical Biology and Bioinformatics. 12(1).