Multiway modeling and analysis in stem cell systems biology.
Multiway modeling and analysis in stem cell systems biology.
复制标题
干细胞系统生物学中的多路建模和分析。
DOI：
10.1186/1752-0509-2-63
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发表时间：
2008-07-14
影响因子：
--
通讯作者：
Plopper GE
中科院分区：
文献类型：
--
作者：
Yener B;Acar E;Aguis P;Bennett K;Vandenberg SL;Plopper GE
系统生物学是指旨在揭示生物系统的新兴特性的多学科方法。干细胞因其广泛的治疗潜力而成为该分析的一个有吸引力的目标。系统生物学的一个中心主题是使用计算模型从大量还原分子数据（例如基因/蛋白质表达、信号转导活动、代谢活动等）中重建复杂系统。许多确定性、概率性和统计学习模型用于理解复杂的细胞行为，例如细胞分化过程中的蛋白质表达和信号网络的活动。然而，这些模型中有许多是双峰的，即它们只考虑行列关系。相比之下，多路建模技术（也称为张量模型）可以分析多模态数据，从而捕获有关细胞分化等复杂行为的更多信息。特别是，张量可以成为对生物网络随时间动态活动进行建模的非常强大的工具。在这里，我们回顾了系统生物学在干细胞中的应用，并举例说明了张量分析在胶原诱导的人间充质干细胞成骨分化模型中的应用。我们应用 Tucker1、Tucker3 和平行因子分析 (PARAFAC) 模型来识别细胞外基质诱导人间充质干细胞成骨分化过程中的蛋白质/基因表达模式。在一种情况下，我们将数据组织成蛋白质/基因位点链接×基因本体类别×成骨刺激剂的张量，并发现我们的细胞在经历成骨分化时表达两组不同的、刺激依赖性的功能相关基因。在第二个案例中，我们以基因 ID × 成骨刺激 × 重复的三向张量组织 DNA 微阵列数据，发现对 I 型胶原基质施加拉伸应变加速了静态 I 型胶原基质诱导的成骨分化。我们的结果提出了基因和蛋白质水平模型，通过该模型干细胞可以转分化为成骨细胞，并为机制、假设驱动的研究奠定基础。我们的分析方法适用于各种干细胞分化模型。
Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate. Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.
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影响因子：
4.4
作者：
Bennett, Kristin P.;Bergeron, Charles;Plopper, George E.
通讯作者：
Plopper, George E.
DOI：
10.1073/pnas.0709146104
发表时间：
2007-11-20
影响因子：
11.1
作者：
Omberg, Larsson;Golub, Gene H.;Alter, Orly
通讯作者：
Alter, Orly
DOI：
10.1165/ajrcmb.23.6.4291
发表时间：
2000-12-01
影响因子：
6.4
作者：
Kaminski, N
通讯作者：
Kaminski, N
DOI：
10.1097/med.0b013e32827035dd
发表时间：
2007-08-01
期刊：
Current opinion in endocrinology, diabetes, and obesity
影响因子：
--
作者：
Jensen, Jan
通讯作者：
Jensen, Jan
影响因子：
3
作者：
KROONENBERG, PM;DELEEUW, J
通讯作者：
DELEEUW, J