Tootfinder

Deep Mapper Graph and its Application to Visualize Plausible Pathways on High-Dimensional Distribution with Small Time-Complexity
Ziyad Oulhaj, Yoshiyuki Ishii, Kento Ohga, Kimihiro Yamazaki, Mutsuyo Wada, Yuhei Umeda, Takashi Kato, Yuichiro Wada, Hiroaki Kurihara
https://arxiv.org/abs/2402.19177…

Deep Mapper Graph and its Application to Visualize Plausible Pathways on High-Dimensional Distribution with Small Time-Complexity
Mapper is a topology based data analysis method that extracts topological features from high-dimensional data. The Mapper algorithm requires a filter function that maps the dataset to a Euclidian space and a clustering method, that is performed on the original dataset. This produces a graph which represents the shape of the original data. In this work, we use Mapper to uncover the conformational change of protein structures and we choose the filter function from a parameterized family, based on…