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Many Paths Lead to Discovery: Analogical Retrieval of Cancer Therapies

机译：许多路径导致发现：癌症治疗的类比检索

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This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS_WITH gene y ASSOCIATED_WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate's Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.
机译：本文通过使用基于量子连接的分离运算符将许多潜在推理途径结合到单个搜索表达式中，解决了模拟推理的问题，以及新的治疗发现的潜在作用。在其中，我们扩展了我们以前的工作，我们使用基于预测的语义索引（PSI）模型进行了类比检索的方法，该模型在高维矢量空间中编码概念和它们之间的关系。与之前的工作一样，我们利用PSI推断连接两个示例概念的谓词途径的能力，在这种情况下包括已知的治疗关系。例如，考虑到药物X治疗疾病Z，我们可能会推断谓词途径药物x相互作用_基因Y相关联_疾病Z，并使用该途径以类似的方式搜索与另一种疾病相关的药物。作为生物学系统倾向于通过关系网络的特征来表征，通过测试不同方法来恢复已知治疗关系的能力，评估量子启发运营商在多种关系中调节推理和检索的能力。此外，我们介绍了一种基于板的圆全息减少表示的新型复杂向量的PSI实现，除了我们在我们以前的研究中应用的基于二元载体的方法外，我们还利用了所有实验。

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