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
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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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Uncover Spatial-Constraint Related Morphome Using Tissue-on-a-Chip Platform and Data-Driven Mathematical Modeling
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