Parameter-less approaches for interpreting dynamic cellular response

Journal of Biological Engineering

Kumar Selvarajoo¹ 

[1] Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan

关键词: Gene expression;    Immune response;    Cell signaling;    Non-parametric;    Biological networks;   

Others  :  1133636
DOI  :  10.1186/1754-1611-8-23

 received in 2014-05-02, accepted in 2014-08-11,  发布年份 2014

【 摘 要 】

Cellular response such as cell signaling is an integral part of information processing in biology. Upon receptor stimulation, numerous intracellular molecules are invoked to trigger the transcription of genes for specific biological purposes, such as growth, differentiation, apoptosis or immune response. How complex are such specialized and sophisticated machinery? Computational modeling is an important tool for investigating dynamic cellular behaviors. Here, I focus on certain types of key signaling pathways that can be interpreted well using simple physical rules based on Boolean logic and linear superposition of response terms. From the examples shown, it is conceivable that for small-scale network modeling, reaction topology, rather than parameter values, is crucial for understanding population-wide cellular behaviors. For large-scale response, non-parametric statistical approaches have proven valuable for revealing emergent properties.

【 授权许可】

   
2014 Selvarajoo; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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