Recently, an increasing number of biological and clinical reports have demonstrated that imbalance of microbial community has the ability to play important roles among several complex diseases in the level of human health. Having a good knowledge of discovery potential of microbe-disease relationships, which provides the ability to having better understanding on some issues, including disease pathology, further boosts disease diagnostics and prognostics, has been taken into account. Nevertheless, a few of computational approaches can meet the need of huge scale of microbe-disease association discovery. In this work, we proposed the EHAI model, which is Enhanced Human microbe-disease Association Identification. EHAI employed the microbe-disease associations, and then Gaussian interaction profile kernel similarity has been utilized to enhance the basic microbe-disease association. Actually, some known microbe-disease associations and a large amount of associations are still unavailable among the datasets. The 'super-microbe' and 'super-disease' were employed to enhance the model. Computational results demonstrated that such super-classes have the ability to be helpful to the performance of EHAI. Therefore, it is anticipated that EHAI can be treated as an important biological tool in this field.

中文翻译：

---

EHAI：增强型人类微生物疾病协会鉴定。

近来，越来越多的生物学和临床报道表明，微生物群落的失衡具有在人类健康水平上的几种复杂疾病之间起重要作用的能力。已经考虑到对微生物疾病关系的发现潜力有很好的了解，这提供了对某些问题（包括疾病病理学）有更好的了解的能力，进一步促进了疾病的诊断和预后。然而，一些计算方法可以满足大规模的微生物-疾病关联发现的需求。在这项工作中，我们提出了EHAI模型，即增强型人类微生物疾病协会鉴定。EHAI雇用了微生物疾病协会，然后利用高斯交互作用谱核相似性来增强基本的微生物-疾病关联。实际上，一些已知的微生物-疾病关联和大量关联仍然在数据集中不可用。采用“超级微生物”和“超级疾病”来增强模型。计算结果表明，此类超类具有帮助EHAI表现的能力。因此，可以预期的是，EHAI可以被视为该领域中的重要生物学工具。计算结果表明，此类超类具有帮助EHAI表现的能力。因此，可以预期的是，EHAI可以被视为该领域中的重要生物学工具。计算结果表明，此类超类具有帮助EHAI表现的能力。因此，可以预期的是，EHAI可以被视为该领域中的重要生物学工具。