微生物基因实体学为人类疾病中的微生物功能发现提供了深度神经网络的信息
Yunjie Liu1, Yao-Zhong Zhang1, Seiya Imoto1
1Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
PloS one
|August 21, 2023
概括
这项研究引入了一种新的神经网络模型,以揭示人类微生物组在糖尿病和IBD等疾病中的功能作用. 该模型确定了关键的微生物基因和功能,为疾病机制提供了新的见解.
科学领域:
- 微生物学 微生物学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 人类微生物组是健康和疾病的组成部分,但其在各种病理中的功能作用难以确定.
- 超基因组数据的高维度和现有模型的有限解释性阻碍了在人类疾病中探索微生物功能.
研究的目的:
- 开发和验证一种新型的神经网络模型,集成基因本体学 (GO) 关系,以阐明人类疾病中的微生物功能.
- 识别和可视化关键的微生物基因及其相关功能,有助于疾病状态.
主要方法:
- 开发了一个包含基因本体学 (GO) 关系网络的神经网络模型.
- 该模型应用于四个基准数据集:糖尿病,肝硬化,炎症性肠病和结直肠癌.
- 基因和GO术语重要性得分被计算为基于网络的发现和可视化.
主要成果:
- 该模型成功地识别和可视化了新的微生物组候选基因及其功能.
- 与非转基因信息模型相比,这种方法提供了更高程度的生物解释性.
- 该模型在测试的数据集中在疾病预测方面表现出了竞争力.
结论:
- 拟议的模型提供了一种强大的方法来揭示人类疾病中的微生物功能.
- 鉴定到的微生物基因和功能为微生物群对疾病发病的贡献提供了新的见解.
- 这项工作推动了我们对人类微生物组在健康和疾病中的作用的理解.
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