Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions

arXiv:2403.00875v1 Announce Type: cross
Abstract: Augmentation is an effective alternative to utilize the small amount of labeled protein data. However, most of the existing work focuses on design-ing new architectures or pre-training tasks, and relatively little work has studied data augmentation for proteins. This paper extends data augmentation techniques previously used for images and texts to proteins and then benchmarks these techniques on a variety of protein-related tasks, providing the first comprehensive evaluation of protein augmentation. Furthermore, we propose two …

abstract architectures arxiv augmentation benchmark cs.ai cs.lg data design ing paper predictive predictive models pre-training protein proteins q-bio.bm q-bio.qm small tasks training type via work