Anderson Oliver, Barelvi Altaf, O'Brien Aden, Norman Ainsley, Jan Iris, Ritz Anna
Biology Department, Reed College, Portland, Oregon, United States of America.
PLoS One. 2025 Sep 5;20(9):e0331280. doi: 10.1371/journal.pone.0331280. eCollection 2025.
Molecular interaction networks are a vital tool for studying biological systems. While many tools exist that visualize a protein or a pathway within a network, no tool provides the ability for a researcher to consider a protein's position in a network in the context of a specific biological process or pathway. We developed ProteinWeaver, a web-based tool designed to visualize and analyze non-human protein interaction networks by integrating known biological functions. ProteinWeaver provides users with an intuitive interface to situate a user-specified protein in a user-provided biological context (as a Gene Ontology term) in seven model organisms. ProteinWeaver also reports the presence of physical and regulatory network motifs within the queried subnetwork and statistics about the protein's distance to the biological process or pathway within the network. These insights can help researchers generate testable hypotheses about the protein's potential role in the process or pathway under study. Two cell biology case studies demonstrate ProteinWeaver's potential to generate hypotheses from the queried subnetworks. ProteinWeaver is available at https://proteinweaver.reedcompbio.org/.
分子相互作用网络是研究生物系统的重要工具。虽然有许多工具可以可视化网络中的蛋白质或信号通路，但没有工具能让研究人员在特定生物过程或信号通路的背景下考虑蛋白质在网络中的位置。我们开发了ProteinWeaver，这是一个基于网络的工具，旨在通过整合已知生物学功能来可视化和分析非人类蛋白质相互作用网络。ProteinWeaver为用户提供了一个直观的界面，以便在七种模式生物中，将用户指定的蛋白质置于用户提供的生物学背景（作为一个基因本体学术语）中。ProteinWeaver还报告了查询子网络中物理和调控网络基序的存在情况，以及关于蛋白质在网络中与生物过程或信号通路距离的统计信息。这些见解可以帮助研究人员对所研究的过程或信号通路中蛋白质的潜在作用提出可检验的假设。两个细胞生物学案例研究证明了ProteinWeaver从查询子网络中生成假设的潜力。可通过https://proteinweaver.reedcompbio.org/访问ProteinWeaver。
