Xing Zenan, Eckhardt James, Vaidya Aditya S, Cutler Sean R
Botany and Plant Sciences, University of California, Riverside, CA, 92521, USA.
Institute for Integrative Genome Biology, University of California, Riverside, CA, 92521, USA.
Plant Methods. 2025 Apr 27;21(1):55. doi: 10.1186/s13007-025-01372-x.
Dose-response and time-to-event data are common in enzymology, pharmacology, and agronomy studies. Diverse biological response curves can be generated from such data. The features of these curves can be elucidated through parameters such as ED (the effective dose that gives 50% of the maximum response) and T (the time required to reach 50% of the maximum response). Properly estimating these parameters is crucial for inferring the potency of compounds or the relative timings of biological processes.
We present an open-source Shiny application, BioCurve Analyzer, that simplifies the process of inferring ED and T parameters from response curves exhibiting various patterns, including classic monotonic sigmoidal curves and more complicated biphasic curves. BioCurve Analyzer provides access to several packages and commonly used models for characterizing response patterns, assists users in identifying the models that best describe their data, and includes options for inferring ED values on both sides of biphasic curves. BioCurve Analyzer also facilitates the visualization of response patterns and allows users to customize their final graphical representation to deliver publication-quality graphs of the data.
BioCurve Analyzer integrates multiple R packages in an easy-to-use web-based interface to facilitate dose-response and time-to-event analyses.
剂量反应和事件发生时间数据在酶学、药理学和农学研究中很常见。从这些数据中可以生成各种生物反应曲线。这些曲线的特征可以通过诸如ED（产生最大反应50%的有效剂量）和T（达到最大反应50%所需的时间）等参数来阐明。正确估计这些参数对于推断化合物的效力或生物过程的相对时间至关重要。
我们展示了一个开源的Shiny应用程序BioCurve Analyzer，它简化了从呈现各种模式的反应曲线（包括经典的单调S形曲线和更复杂的双相曲线）推断ED和T参数的过程。BioCurve Analyzer提供了对几个用于表征反应模式的软件包和常用模型的访问，帮助用户识别最能描述其数据的模型，并包括在双相曲线两侧推断ED值的选项。BioCurve Analyzer还便于反应模式的可视化，并允许用户自定义其最终的图形表示，以提供具有发表质量的数据图。
BioCurve Analyzer在易于使用的基于网络的界面中集成了多个R软件包，以促进剂量反应和事件发生时间分析。
