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| 1 | Prediction of Protein-Protein Interactions by a Novel Model Based on Domain Information显示文摘Domain-based protein-protein interactions( PPIs) is a problem that has drawn the attentions of many researchers in recent years and it has been studied using lots of computational approaches from many different perspectives. Existing domain-based methods to predict PPIs typically infer domain interactions from known interacting sets of proteins. However,these methods are costly and complex to implement. In this paper, a simple and effective prediction model is proposed. In this model,an improved multiinstance learning( MIL) algorithm( MilCaA) is designed that doesn't need to take the domain interactions into consideration to construct MIL bags. Then, the pseudo-amino acid composition( PseAAC) transformation method is used to encode the instances in a multi-instance bag and the principal components analysis( PCA) is also used to reduce the feature dimension. Finally, several traditional machine learning and MIL methods are used to verify the proposed model. Experimental results demonstrate that MilCaA performs better than state-of-the-art techniques including the traditional machine learning methods which are widely used in PPIs prediction. | 董露露 谢飞 章程 李斌 | 2018 | Journal of Donghua University(English Edition)2018，35，2： | 0 |
| 2 | 基于商空间粒度计算的资源检索技术研究显示文摘针对现今互联网海量资源,资源检索速度越来越慢,资源库硬件成本越来越高昂的特点,论文提出基于商空间粒度计算的资源检索技术,通过对资源库分层递阶,从粗到细、逐步求精的检索方式,相对于传统检索方式——检索资源总库的检索方式,大大提高了使用者的检索效率。实验结果表明,基于商空间粒度计算的资源检索模式能更加高效高质地完成使用者的资源检索需求。 | 孙维智 邓婵 | 2020 | 计算机与数字工程2020，48，9： | 0 |
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