Frédérique Lisacek

The paper trains a hybrid neural network to predict N-glycosylation events and structures from protein sequences using glycosite-flanking data, demonstrating its ability to predict glycan composition and abundance.

The paper identifies a relationship between protein structure and glycan structure, introducing a glycoimpact matrix to predict glycosylation patterns and validate it through disease variants and engineered antibodies.

This paper introduces GlycoQL, a query language for glycan structure search, and demonstrates its use in analyzing SARS-CoV-2 spike protein glycosylation.

LectinOracle predicts lectin-glycan interactions using deep learning, showing agreement with literature and generalizing to new glycans and lectins.

The paper predicts bacterial carbohydrate-binding proteins (lectins) across genomes to explore their role in vaginal microbiome colonization and pathogenicity.

The paper surveys fungal lectins through phylogenetic analysis and bioinformatics, identifying 33,485 putative lectin sequences across 1,223 fungal species.

The paper introduces GlyConnect Compozitor, a tool for visualizing and comparing glycan compositions to aid in selecting appropriate compositions for glycoproteomics analysis.

The paper describes an e-infrastructure for recording glycomic mass spectrometric data in compliance with MIRAGE reporting guidelines, enabling standardized data submission to a public repository.