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Learning a Mechanical Growth Model of Flower Morphogenesis

Argyris Zardilis, Alexandra Budnikova,Henrik Jönsson

biorxiv(2025)

University of Cambridge

Cited 0|Views2
Abstract
Morphogenesis, the process by which organs take their shape, is a fundamental problem in biology and requires a complex combination of genetic, biochemical, and mechanical signals. The data that we collect for this process are usually multi-scale and multi-modal, typically image timeseries of tissue morphology and transcription data. As the data becomes larger and more diverse, the harder it becomes to gain meaningful understanding in terms of theoretical models. Here, and tackling this problem in the developing flower organ, we learn a mechanical model of growth starting from combined morphology and transcription data across the tissue by firstly learning and connecting independent representations for the two spaces and secondly refining the representation using the mechanical state of the tissue to learn a mechanical growth model. This approach can link multiple scales, in this case proposing the physical action of genes, and can act as a vehicle to accommodate diverse data and hypotheses in developmental biology of plants and beyond. ### Competing Interest Statement The authors have declared no competing interest.
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要点】:本文提出了一种结合形态学和转录数据,通过学习组织力学状态,建立花朵发育过程中的机械生长模型的方法,以链接多尺度数据并促进发育生物学研究。

方法】:作者首先学习并连接形态学和转录数据的独立表示,然后通过考虑组织的力学状态来精炼表示,从而学习出机械生长模型。

实验】:实验通过结合不同时间点的组织形态和转录数据,使用该方法成功建立了花朵器官发育的机械模型,具体数据集名称未在摘要中提及。