Model Abstraction and Temporal Behavior Analysis of Genetic Regulatory Networks
Model Abstraction and Temporal Behavior Analysis of Genetic Regulatory Networks
复制标题
遗传调控网络的模型抽象和时间行为分析
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Hiroyuki Kuwahara
中科院分区：
文献类型：
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作者：
Hiroyuki Kuwahara
随着高通量数据收集和基因组测序方法等技术的进步，确定人类DNA序列并确定人类DNA中所有基因的人类基因组计划至少提前两年完成。随着这些技术变得更加准确、高效和经济，以及大量的基因组和蛋白质组学数据正以快速的速度变得可用，我们现在面临的挑战是了解这些基因如何与环境刺激结合在一起协调细胞水平行为的调节。然而，理解这样复杂的系统是非常昂贵的，而且很可能仅仅通过湿实验室实验是不切实际的，因为数据的数量和复杂性大大增加，需要集成计算方法以使过程更有效。
With advances in technologies such as high throughput data collection and genome sequencing methods, the Human Genome Project which, among other things, determined the human DNA sequence and identified all the genes in human DNA was completed at least two years ahead of time. As these technologies are becoming more accurate, efficient, and cost effective and a massive amount of genomic and proteomic data are becoming available at a rapid pace, we are now in the position to face the challenge to understand how these genes coupled with environmental stimuli orchestrate the regulation of cell-level behaviors. However, understanding such complex systems is very expensive and is most likely impractical with wet-lab experiments alone as the amount and the complexity of data substantially increase, requiring the integration of computational methods to make the process more efficient.
To allow for substantial acceleration in computational analysis, this dissertation develops a model abstraction methodology for biochemical systems which systematically performs various model abstractions to reduce the complexity of computational biochemical models. Our methodology is particularly useful for systems with small molecular counts that require the discrete and stochastic representation and thus demand substantial computational requirements. As a case study, this dissertation illustrates the application of individual abstraction methods to such systems. Furthermore, it demonstrates the application of collective abstraction methods at various accuracy levels to temporal behavior analysis of several genetic regulatory networks. This dissertation shows that analysis time of biologically relevant properties of such genetic regulatory networks can be improved from days of work to minutes of work using our methodology while maintaining reasonable accuracy.
大肠杆菌 lrp 基因的调节。
影响因子：
3.2
作者：
Wang,Q;Wu,J;Friedberg,D;Plakto,J;Calvo,JM
通讯作者：
Calvo,JM
影响因子：
56.9
作者：
DeRisi, JL;Iyer, VR;Brown, PO
通讯作者：
Brown, PO
影响因子：
5.6
作者：
SHEA, MA;ACKERS, GK
通讯作者：
ACKERS, GK