M

metric-learning

This repository contains data and code utilized for the metric-learning based classification of the “human E3 ligome”–an extensive set of catalytic human E3s–by integrating multi-layered data, including protein sequences, domain architectures, 3D structures, functions, and expression pattern. Manuscript: https://www.biorxiv.org/content/10.1101/2025.03.09.642240v1.full.pdf

In facestretch we describe how we exploited the dlib’s facial landmarks in order to measure face deformation and perform an expression recognition task. We implemented multiple approaches, based metric learning, neural networks and geodesic distances