UNASSIGNED: This commentary aims to deepen the understanding of class-based approaches by elucidating the pivotal role of chemical similarity (structural and biological) in clustering and classification approaches (CCAs). It addresses the dichotomy between general end point-agnostic similarity, often entailing unsupervised analysis, and end point-specific similarity necessitating supervised learning. The goal is to highlight the nuances of these approaches, their applications, and common misuses.
UNASSIGNED: Understanding similarity is pivotal in toxicological research involving CCAs. The effectiveness of these approaches depends on the right definition and measure of similarity, which varies based on context and objectives of the study. This choice is influenced by how chemical structures are represented and the respective labels indicating biological activity, if applicable. The distinction between unsupervised clustering and supervised classification methods is vital, requiring the use of end point-agnostic vs. end point-specific similarity definition. Separate use or combination of these methods requires careful consideration to prevent bias and ensure relevance for the goal of the study. Unsupervised methods use end point-agnostic similarity measures to uncover general structural patterns and relationships, aiding hypothesis generation and facilitating exploration of datasets without the need for predefined labels or explicit guidance. Conversely, supervised techniques demand end point-specific similarity to group chemicals into predefined classes or to train classification models, allowing accurate predictions for new chemicals. Misuse can arise when unsupervised methods are applied to end point-specific contexts, like analog selection in read-across, leading to erroneous conclusions. This commentary provides insights into the significance of similarity and its role in supervised classification and unsupervised clustering approaches. https://doi.org/10.1289/EHP14001.
■本评论旨在通过阐明化学相似性(结构和生物学)在聚类和分类方法(CCA)中的关键作用,加深对基于类别的方法的理解。它解决了一般终点与不可知相似性之间的二分法,通常需要无监督分析,和终点特定的相似性需要监督学习。目标是突出这些方法的细微差别,他们的应用,和常见的误用。
■了解相似性对于涉及CCA的毒理学研究至关重要。这些方法的有效性取决于相似性的正确定义和度量,这取决于研究的背景和目标。这种选择受到化学结构如何表示和指示生物活性的相应标签的影响。如果适用。无监督聚类和监督分类方法之间的区别至关重要,要求使用终点不可知与端点特定的相似性定义。这些方法的单独使用或组合需要仔细考虑,以防止偏见并确保与研究目标的相关性。无监督方法使用终点不可知的相似性度量来揭示一般的结构模式和关系,帮助假设生成并促进数据集的探索,而无需预定义的标签或明确的指导。相反,监督技术要求特定于终点的相似性,将化学品分为预定义的类别或训练分类模型,允许对新的化学物质进行准确的预测。当将无监督方法应用于特定于终点的上下文时,可能会出现误用,比如阅读中的模拟选择,导致错误的结论。这篇评论提供了对相似性的重要性及其在监督分类和无监督聚类方法中的作用的见解。https://doi.org/10.1289/EHP14001.