Bacterial artificial chromosome (BAC) is a kind of vector system used to construct large fragment insert libraries of genome DNA in human, animals and plants.

细菌人工染色体(BAC)是一种承载dna大片段的克隆载体系统，用于人、动物和植物基因组文库构建。

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Objective: to investigate the potential of learning vector quantization (LVQ) artificial neural network tools for discrimination and forecasting of occurrent intensity of typhoid and paratyphoid.

目的：探讨学习矢量量化(LVQ)人工神经网络在伤寒、副伤寒发生强度判别与预测中的应用。

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Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.

与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。

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