Literature DB >> 22492637

On the calculation of signal transduction ability of signaling transduction pathways in intracellular communication: systematic approach.

Bor-Sen Chen1, Chia-Chou Wu.   

Abstract

MOTIVATION: The major function of signal transduction pathways in cells is to sense signals from the environment and process the information through signaling molecules in order to regulate the activity of transcription factors. On the molecular level, the information transmitted by a small number of signal molecules is amplified in the internal signaling pathway through enzyme catalysis, molecular modification and via the activation or inhibition of interactions. However, the dynamic system behavior of a signaling pathway can be complex and, despite knowledge of the pathway components and interactions, it is still a challenge to interpret the pathways behavior. Therefore, a systematic method is proposed in this study to quantify the signal transduction ability.
RESULTS: Based on the non-linear signal transduction system, signal transduction ability can be investigated by solving a Hamilton-Jacobi inequality (HJI)-constrained optimization problem. To avoid difficulties associated with solving a complex HJI-constrained optimization problem for signal transduction ability, the Takagi-Sugeno fuzzy model is introduced to approximate the non-linear signal transduction system by interpolating several local linear systems so that the HJI-constrained optimization problem can be replaced by a linear matrix inequality (LMI)-constrained optimization problem. The LMI problem can then be efficiently solved for measuring signal transduction ability. Finally, the signal transduction ability of two important signal transduction pathways was measured by the proposed method and confirmed using experimental data, which is useful for biotechnological and therapeutic application and drug design.

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Year:  2012        PMID: 22492637     DOI: 10.1093/bioinformatics/bts159

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  Measuring information flow in cellular networks by the systems biology method through microarray data.

Authors:  Bor-Sen Chen; Cheng-Wei Li
Journal:  Front Plant Sci       Date:  2015-06-02       Impact factor: 5.753

2.  Mathematical model of TGF-βsignalling: feedback coupling is consistent with signal switching.

Authors:  Shabnam Khatibi; Hong-Jian Zhu; John Wagner; Chin Wee Tan; Jonathan H Manton; Antony W Burgess
Journal:  BMC Syst Biol       Date:  2017-04-13

3.  Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Authors:  Bor-Sen Chen; Chia-Chou Wu
Journal:  Cells       Date:  2013-10-11       Impact factor: 6.600

  3 in total

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