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Assessing network-based methods in the context of system toxicology

计算机科学 背景(考古学) 水准点(测量) 机制(生物学) 生化工程 风险分析(工程) 计算生物学 数据挖掘 机器学习 医学 生物 古生物学 哲学 大地测量学 认识论 工程类 地理
作者
Jordi Valls-Margarit,Janet Pińero,Barbara Füzi,Natacha Cerisier,Olivier Taboureau,Laura I. Furlong
出处
期刊:Frontiers in Pharmacology [Frontiers Media SA]
卷期号:14
标识
DOI:10.3389/fphar.2023.1225697
摘要

Introduction: Network-based methods are promising approaches in systems toxicology because they can be used to predict the effects of drugs and chemicals on health, to elucidate the mode of action of compounds, and to identify biomarkers of toxicity. Over the years, the network biology community has developed a wide range of methods, and users are faced with the task of choosing the most appropriate method for their own application. Furthermore, the advantages and limitations of each method are difficult to determine without a proper standard and comparative evaluation of their performance. This study aims to evaluate different network-based methods that can be used to gain biological insight into the mechanisms of drug toxicity, using valproic acid (VPA)-induced liver steatosis as a benchmark. Methods: We provide a comprehensive analysis of the results produced by each method and highlight the fact that the experimental design (how the method is applied) is relevant in addition to the method specifications. We also contribute with a systematic methodology to analyse the results of the methods individually and in a comparative manner. Results: Our results show that the evaluated tools differ in their performance against the benchmark and in their ability to provide novel insights into the mechanism of adverse effects of the drug. We also suggest that aggregation of the results provided by different methods provides a more confident set of candidate genes and processes to further the knowledge of the drug’s mechanism of action. Discussion: By providing a detailed and systematic analysis of the results of different network-based tools, we aim to assist users in making informed decisions about the most appropriate method for systems toxicology applications.
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