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A novel method for multifactorial bio-chemical experiments design based on combinational design theory

机译:基于组合设计理论的多元生化实验设计新方法

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摘要

Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of “balance” in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.
机译:实验设计着重于描述或解释假设的多因素相互作用以反映变化。该设计引入了可能直接影响变化的条件,在此情况下,有选择地选择特定条件进行观察。组合设计理论涉及有限集系统的存在,构造和性质,其排列满足平衡和/或对称的广义概念。在这项工作中,借鉴了组合设计理论中的“平衡”概念,提出了一种用于多因素生化实验设计的新方法,其中在组合设计中使用平衡模板来选择观察条件。涵盖所有影响实验因素的平衡实验数据可以用于进一步处理,例如用于机器学习模型的训练集。最后,开发了一种基于所提出方法的软件来设计实验,该实验可以覆盖一定次数的影响因素。

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