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Network-based Analysis of Kinetics and Regulation

基于网络的动力学和调控分析

基本信息

批准号：
8244434
负责人：
BERNHARD O PALSSON
金额：
$ 32.1万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-07-15 至 2014-03-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Project Summary A growing number of reconstructed metabolic reaction networks have appeared in recent years. Such reconstruction can be converted into a mathematical format that in turn can be used to analyze the properties of the networks. Genome-scale analysis of network properties leads to understanding of their normal physiological functions and malfunction leading to pathophysiological states. The first part of this R01 program was focused on the analysis of possible steady state flux distributions of metabolic networks using extreme pathways. This analysis has proven useful for a number of purposes but is limited in scope. Fortunately, we have found random sampling of the solution space to be a viable and useful alternative to extreme pathways. During the second part of this program we propose to 1) develop uniform randomized sampling of the feasible steady state solution spaces, 2) to apply these algorithms to a series of biological and medical examples, and 3) develop time-scale decomposition of large- scale kinetic models. If the proposed program is successfully executed it will advance the state of the art of building genome-scale models to account for concentrations and to develop first-pass network-scale dynamic models. The availability of such genome-scale models would expand their scope of predictions and thus their applications to various biological and health care issues. PUBLIC HEALTH RELEVANCE: Project Narrative Public investment in DNA sequencing has led to the sequencing of entire genomes of a growing number of organisms. Scientists have determined how to assemble the information found in genomic sequences, along with data from the scientific literature, into the biochemical reaction networks that underlie cellular functions. This process is particularly advanced for metabolism; this proposal is focused on the mathematical description and analysis of metabolic functions in health and disease.

描述（由申请人提供）：项目概述近年来出现了越来越多的重建代谢反应网络。这种重建可以转换为数学格式，进而可以用于分析网络的属性。网络特性的基因组尺度分析导致对其正常生理功能和导致病理生理状态的故障的理解。这个R 01程序的第一部分集中在使用极端途径的代谢网络的可能的稳态通量分布的分析。这一分析已证明对若干目的有用，但范围有限。幸运的是，我们已经发现解决方案空间的随机抽样是极端路径的可行且有用的替代方案。在该计划的第二部分，我们建议1）开发可行的稳态解空间的均匀随机采样，2）将这些算法应用于一系列生物和医学实例，3）开发大规模动力学模型的时间尺度分解。如果拟议的计划成功执行，它将推进建立基因组规模模型的最新技术，以解释浓度和开发首过网络规模的动态模型。这种基因组规模模型的可用性将扩大其预测范围，从而扩大其在各种生物和医疗保健问题上的应用。公共卫生关系：在DNA测序方面的公共投资已经导致越来越多的生物体的整个基因组的测序。科学家们已经确定了如何将基因组序列中发现的信息与科学文献中的数据沿着组装到构成细胞功能基础的生化反应网络中。这个过程是特别先进的代谢;这个建议是集中在数学描述和分析代谢功能的健康和疾病。

项目成果

期刊论文数量（22）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Identification of potential pathway mediation targets in Toll-like receptor signaling.

DOI：
10.1371/journal.pcbi.1000292
发表时间：
2009-02
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Li F;Thiele I;Jamshidi N;Palsson BØ
通讯作者：
Palsson BØ

Large-scale in silico modeling of metabolic interactions between cell types in the human brain.

DOI：
10.1038/nbt.1711
发表时间：
2010-12
期刊：
Nature biotechnology
影响因子：
46.9
作者：
通讯作者：

Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis.

DOI：
10.1038/ncomms8101
发表时间：
2015-06-09
期刊：
NATURE COMMUNICATIONS
影响因子：
16.6
作者：
Zielinski, Daniel C.;Filipp, Fabian V.;Bordbar, Aarash;Jensen, Kasper;Smith, Jeffrey W.;Herrgard, Markus J.;Mo, Monica L.;Palsson, Bernhard O.
通讯作者：
Palsson, Bernhard O.

Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition.

使用随机抽样和奇异值分解的人类红细胞中代谢调节的网络级分析。