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An Immunity Network with Provision for Diverse Recognition in T-Cell Receptors

机译:在T细胞受体中具有多种识别功能的免疫网络

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Recently, biological superior information processing ability has been researched to be able to be useful for a computer system. In particular, neural networks for the brain and nervous system have been researched. Immunity network models based on the biological immune response network also have been studied, but most of the researchers consider only a basic part of the interaction between B cells and T cells. Recent research has reported that the function of T cell receptors (TCR) is important in the practical immune response network. Therefore, we propose a new immunity network model which, unlike the traditional immunity networks, has the same function as that of a TCR. We applied the proposed immunity network model and the traditional immunity network model to the pattern recognition system. And we compared the performance of the proposed immunity network model with the traditional immunity network model, and showed the usability of the proposed immunity network model.
机译:近来,已经研究了生物学上优异的信息处理能力以能够用于计算机系统。特别地,已经研究了用于大脑和神经系统的神经网络。也已经研究了基于生物免疫反应网络的免疫网络模型,但是大多数研究人员仅考虑B细胞和T细胞之间相互作用的基本部分。最近的研究报道,T细胞受体(TCR)的功能在实际的免疫反应网络中很重要。因此,我们提出了一种新的免疫网络模型,与传统的免疫网络不同,该模型具有与TCR相同的功能。我们将提出的免疫网络模型和传统的免疫网络模型应用于模式识别系统。并且我们将提出的免疫网络模型与传统的免疫网络模型的性能进行了比较,并证明了提出的免疫网络模型的可用性。

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