Sriram Neelamegham

GlycoEnzDB curates and presents human glycoenzyme data, linking enzyme functions, pathways, and expression data with external resources and AI-generated descriptions.

This paper introduces GlycoBERT and GlycoBART, transformer-based models for glycan structure prediction from MS/MS data, achieving high accuracy and enabling de novo structure inference.

The paper investigates the functional role of N-glycans in the S2 domain of beta-coronavirus spike proteins, showing their conservation across SARS-CoV-2, SARS-CoV, and MERS-CoV.

This paper identifies glycocalyx thickness as a targetable physical phenotype and demonstrates that castanospermine reduces it, enhancing CAR-T cell efficacy against gastric cancer.

The paper analyzes single-cell glycogene expression in human tissues to identify cell- and tissue-specific glycosylation pathways and transcription factor regulation.

This paper presents an optimized protocol for generating spike trans-complemented SARS-CoV-2 replicons with single-cycle infectivity in BSL-2 settings.

GlycoEnzOnto curates 386 human glycoEnzymes across 135 pathways and 134 molecular functions to improve glycosylation pathway analysis.

This paper predicts tissue-specific transcription factors and signaling pathways regulating glycan biosynthesis using multi-omics data across 29 cancer types.

This paper extends Linear Code to represent reaction rules in glycobiology, aiming to improve consistency and interoperability in glycan synthesis models.