人类微生物组在人类健康中起着至关重要的作用，并与多种人类疾病相关。由于元基因组基因特征的高维度，确定微生物组在人类疾病中的功能角色仍然是一个生物学挑战。然而，现有的模型在提供生物学可解释性方面存在局限性，微生物在人类疾病中的功能角色尚未被探索。在这里，我们提出利用基因本体（Gene Ontology，GO）关系网络并结合基于神经网络的模型来发现微生物在人类疾病中的功能。我们使用了四个基准数据集，包括糖尿病、肝硬化、炎症性肠病和结直肠癌，来探索微生物在人类疾病中的功能。我们的模型通过计算网络中每个基因和GO术语的重要得分，发现并可视化了重要的微生物组基因及其功能的新候选者。此外，我们证明了我们的模型在预测疾病方面与其他非基因本体相关模型相比具有竞争力的表现。这些发现的重要微生物组基因及其功能为微生物的功能贡献提供了新的见解。版权：©2023年Liu等。本文为开放获取文章，根据知识共享署名许可协议进行分发，允许在任何媒介下进行无限制的使用、分发和复制，只要原创作者和来源被给予适当的署名。

The human microbiome plays a crucial role in human health and is associated with a number of human diseases. Determining microbiome functional roles in human diseases remains a biological challenge due to the high dimensionality of metagenome gene features. However, existing models were limited in providing biological interpretability, where the functional role of microbes in human diseases is unexplored. Here we propose to utilize a neural network-based model incorporating Gene Ontology (GO) relationship network to discover the microbe functionality in human diseases. We use four benchmark datasets, including diabetes, liver cirrhosis, inflammatory bowel disease, and colorectal cancer, to explore the microbe functionality in the human diseases. Our model discovered and visualized the novel candidates' important microbiome genes and their functions by calculating the important score of each gene and GO term in the network. Furthermore, we demonstrate that our model achieves a competitive performance in predicting the disease by comparison with other non-Gene Ontology informed models. The discovered candidates' important microbiome genes and their functions provide novel insights into microbe functional contribution.Copyright: © 2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.