Uncover Spatial-Constraint Related Morphome Using Tissue-on-a-Chip Platform and Data-Driven Mathematical Modeling
Uncover Spatial-Constraint Related Morphome Using Tissue-on-a-Chip Platform and Data-Driven Mathematical Modeling
批准号:
10478247
负责人:
Yu Huang
金额:
$35.71万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2026-08-31
关键词:
AddressAreaBehaviorBiologicalBiological ProcessBiological SciencesBiophysicsBrainCell membraneComplexDataDevelopmentEpigenetic ProcessGeneticIn VitroMachine LearningMembraneModelingMolecularMorphologyProcessShapesStimulusSystemTissuesWorkbiological systemscell behaviorcraniumdata-driven modelfascinatein vivoin vivo Modelinterstitialmathematical modeltool
中文摘要
项目总结
细胞行为和组织发育通常在空间限制下发生(例如,
间质间隙、组织衬里、头盖骨封闭)。目前的体外系统通常是
开放培养,因此错过了空间限制和其他体内刺激。这个
目前的体内模型通常是低吞吐量和难以追踪的,因此无法
揭开内在影响(如遗传学/表观遗传学)之间复杂的相互作用
外在因素(如微环境)。例如,细胞膜的起泡和
脑折叠是空间约束下最基本、最有影响力的生物行为。
它们的生物物理和分子机制还不是很清楚。最近,有几个
实验和理论工具的出现吸引了复杂结构的建模
生物行为。
这项拟议的研究旨在将形态信息参数化,与
在空间约束下的复杂影响,并揭示了生物多样性的机制。
这两个领域的行为都是例证。它将通过一个形态组平台完成
它集成了几种实验理论工具(例如,芯片上组织、数据驱动
建模、机器学习),这是PI和Co-IS预先定义的。我们希望
1)填补我们对膜起泡和脑折叠的理解中的显著空白
流程和2)建立有效的战略,以发现广泛的基本
生物过程。
英文摘要
PROJECT SUMMARY
Cell behaviors and tissue developments often occur under spatial constraints (e.g.,
interstitial space, tissue lining, skull enclosure). The current in vitro systems are often
open cultures, and thus miss the spatial constraints and other in vivo stimuli. The
current in vivo models are often low throughput and hard-to-trace, therefore unable to
unravel the complex interplay between intrinsic influences (e.g., genetics/epigenetics)
and extrinsic ones (e.g., micro-environment). For example, cell membrane blebbing and
brain folding are fundamental and impactful bio-behaviors under spatial constraints.
Their biophysical and molecular mechanisms are not well understood. Lately, several
experimental and theoretical tools have emerged to fascinate the modeling of complex
bio-behaviors.
This proposed study aims to parameterize morphological information, relate to the
complex influences under spatial constraints, and unravel the mechanism of bio-
behaviors in the two exemplified areas. It will be done through a morphome platform
that integrates several experimental-theoretical tools (e.g., tissue-on-a-chip, data-driven
modeling, machine-learning), which has been pre-defined by PI and Co-Is. We hope to
1) fill the compelling gaps in our understanding of membrane blebbing and brain folding
process and 2) establish an effective strategy to uncover a broad range of basic
biological processes.
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