Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis
المؤلفون المشاركون
Zou, Xiufen
Wang, Gang
Li, Yuanyuan
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-08-01
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Many complex diseases (chronic disease onset, development and differentiation, self-assembly, etc.) are reminiscent of phase transitions in a dynamical system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system.
Understanding such nonlinear behaviors is critical to dissect the multiple genetic/environmental factors that together shape the genetic and physiological landscape underlying basic biological functions and to identify the key driving molecules.
Based on stochastic differential equation (SDE) model, we theoretically derive three statistical indicators, that is, coefficient of variation (CV), transformed Pearson’s correlation coefficient (TPC), and transformed probability distribution (TPD), to identify critical transitions and detect the early-warning signals of the phase transition in complex diseases.
To verify the effectiveness of these early-warning indexes, we use high-throughput data for three complex diseases, including influenza caused by either H3N2 or H1N1 and acute lung injury, to extract the dynamical network biomarkers (DNBs) responsible for catastrophic transition into the disease state from predisease state.
The numerical results indicate that the derived indicators provide a data-based quantitative analysis for early-warning signals for critical transitions in complex diseases or other dynamical systems.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Gang& Li, Yuanyuan& Zou, Xiufen. 2017. Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1142305
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Gang…[et al.]. Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1142305
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Gang& Li, Yuanyuan& Zou, Xiufen. Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1142305
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1142305
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر