Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders
Graph masked autoencoders (GMAE) have emerged as a significant advancement in self-
supervised pre-training for graph-structured data. Previous GMAE models primarily utilize a …
supervised pre-training for graph-structured data. Previous GMAE models primarily utilize a …
Complementary multi-modality molecular self-supervised learning via non-overlapping masking for property prediction
Self-supervised learning plays an important role in molecular representation learning
because labeled molecular data are usually limited in many tasks, such as chemical …
because labeled molecular data are usually limited in many tasks, such as chemical …
Hi-GMAE: Hierarchical Graph Masked Autoencoders
Graph Masked Autoencoders (GMAEs) have emerged as a notable self-supervised learning
approach for graph-structured data. Existing GMAE models primarily focus on reconstructing …
approach for graph-structured data. Existing GMAE models primarily focus on reconstructing …
SS-Pro: a simplified Siamese contrastive learning approach for protein surface representation
Conclusion In this paper, we introduce a simple Siamese contrastive self-supervised
learning framework for protein surface representation learning. The encoder in this …
learning framework for protein surface representation learning. The encoder in this …
The power and limits of predicting exon-exon interactions using protein 3D structures
J Liebold, A Del Moral-Morales, K Manalastas-Cantos… - bioRxiv, 2024 - biorxiv.org
Alternative splicing (AS) effects on cellular functions can be captured by studying changes in
the underlying protein-protein interactions (PPIs). Because AS results in the gain or loss of …
the underlying protein-protein interactions (PPIs). Because AS results in the gain or loss of …