MotorBench: A Cryo-Electron Tomography Dataset of Bacterial Flagellar Motors for Testing Detection Algorithms

Abstract

Understanding bacterial nanomachines like flagellar motors, which are crucial for pathogenic bacteria motility, is vital for microbiological and therapeutic research. Cryogenic electron tomography (cryo-ET) enables visualization of these structures within cells at near-native conditions. But manual identification remains challenging due to low contrast, limited resolution, and crowded in vivo environments. To address this, we introduce MotorBench, an expert-annotated dataset of bacterial flagellar motors that has been curated as part of a Kaggle competition BYU - Locating Bacterial Flagellar Motors 2025, engaging data scientists globally to create automated detection algorithms. MotorBench and its accompanying tools are intended to serve as a benchmark for evaluating and comparing future algorithms in automated cryo-ET analysis.