Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces.

V Chandana Epa, Jing Yang, Ying Mei, Andrew L Hook, Robert Langer, Daniel G Anderson, Martyn C Davies, Morgan R Alexander, David A Winkler
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引用次数: 41

Abstract

Designing materials to control biology is an intense focus of biomaterials and regenerative medicine research. Discovering and designing materials with appropriate biological compatibility or active control of cells and tissues is being increasingly undertaken using high throughput synthesis and assessment methods. We report a relatively simple but powerful machine-learning method of generating models that link microscopic or molecular properties of polymers or other materials to their biological effects. We illustrate the potential of these methods by developing the first robust, predictive, quantitative, and purely computational models of adhesion of human embryonic stem cell embryoid bodies (hEB) to the surfaces of a 496-member polymer micro array library.

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模拟人类胚状体细胞粘附到组合库的聚合物表面。
设计控制生物学的材料是生物材料和再生医学研究的一个热点。使用高通量合成和评估方法,发现和设计具有适当生物相容性或对细胞和组织有活性控制的材料正在越来越多地进行。我们报告了一种相对简单但功能强大的机器学习方法,用于生成将聚合物或其他材料的微观或分子特性与其生物效应联系起来的模型。我们通过开发人类胚胎干细胞胚状体(hEB)与496个聚合物微阵列文库表面粘附的第一个稳健、预测、定量和纯计算模型来说明这些方法的潜力。
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来源期刊
Journal of Materials Chemistry
Journal of Materials Chemistry 工程技术-材料科学:综合
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