A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data
Joint Authors
Li, Xianhua
Ribaudo, Nicholas
Huang, Zuyi (Jacky)
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-29
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Detection of malfunctioning reactions or molecules from clinical data is essential for disease treatments.
In order to find an alternative to the existing oversimplistic mathematical models, a kinetic model is developed in this work to infer the malfunctioning reactions/molecules by quantifying the similarity between the clinical profile and the output profiles predicted from the model in which certain reactions/molecules malfunction.
The new approach was tested in IL-6 and TNF-α/NF-κB signaling pathway, for four abnormal conditions including up/downregulation of single reaction rate constants and up/downregulation of single molecules.
Since limited quantitative clinical data were available, the IL-6 ODE model was used to generate artificial clinical data for the abnormal steady-state value shown in two key molecules: nuclear STAT3 and SOCS3.
Similarly, the TNF-α/NF-κB model was used to obtain the data in which abnormal oscillation dynamic was shown in the profile of NF-κB.
The results show that the approach developed in this study was able to successfully identify the malfunctioning reactions and molecules from the clinical data.
It was also found that this new approach was noise-robust and that it managed to reveal unique solution for the faulty components in a network.
American Psychological Association (APA)
Li, Xianhua& Ribaudo, Nicholas& Huang, Zuyi (Jacky). 2015. A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data. BioMed Research International،Vol. 2015, no. 2015, pp.1-19.
https://search.emarefa.net/detail/BIM-1055398
Modern Language Association (MLA)
Li, Xianhua…[et al.]. A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data. BioMed Research International No. 2015 (2015), pp.1-19.
https://search.emarefa.net/detail/BIM-1055398
American Medical Association (AMA)
Li, Xianhua& Ribaudo, Nicholas& Huang, Zuyi (Jacky). A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-19.
https://search.emarefa.net/detail/BIM-1055398
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1055398