MetaMDA:利用微生物-代谢物-药物异质网络上的随机走路来解释微生物-药物协会的预测
Qi Wang1, Shuting Chen1, Xintian Miao1
1School of Mathematics, Shandong University, Jinan, Shandong 250100, China.
Bioinformatics (Oxford, England)
|December 1, 2025
概括
使用一种新的网络方法,MetaMDA预测了微生物与药物之间的关联 (MDA). 该框架通过准确识别新的MDA和揭示潜在的生物机制,增强了药物发现.
科学领域:
- 计算生物学是一种计算生物学.
- 微生物组研究的研究.
- 药理学 药理学是指药理学的学科.
背景情况:
- 微生物影响人类健康和疾病,包括癌症.
- 预测微生物药物协会 (MDA) 对药物发现和个性化医学至关重要.
- 现有的方法与新型微生物/药物作斗争,缺乏机械洞察力.
研究的目的:
- 开发一个计算框架,MetaMDA,用于预测MDA.
- 模拟微生物,代谢物和药物之间的复杂生物相互作用.
- 克服现有方法在预测新兴关联和理解机制方面的局限性.
主要方法:
- 构建了一个整合微生物,代谢物和药物的异质图.
- 采用随机步行算法,在图表上定制过渡概率.
- 在统一的尺度上捕获多式联络节点特征,用于预测.
主要成果:
- MetaMDA的性能平均比最先进的方法高出26%.
- 预测涉及以前未见的微生物或药物的MDA的能力.
- 为特定的微生物药物协会提供了机制性解释,例如,大肠杆菌和埃斯基塔洛普拉姆.
结论:
- 为了预测MDA,MetaMDA提供了一个强大的计算方法.
- 该框架通过识别新的关联和阐明机制来推动药物发现.
- 在健康和疾病中,MetaMDA有潜力更深入地了解微生物与药物相互作用.
相关概念视频
Protein Networks
4.5K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.5K
Mechanistic Models: Overview of Compartment Models
334
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
334
Pharmacokinetic Models: Overview
1.8K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.8K
Mechanistic Models: Compartment Models in Individual and Population Analysis
226
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
226
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
223
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
223
Analysis of Population Pharmacokinetic Data
657
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
657


