Gilbert S. Omenn

The paper introduces the Vaccine Ontology (VO), a standardized framework for representing vaccines and related data, enhancing data integration and AI research.

The paper predicts the structural impact of human alternative splicing using AlphaFold2 on over 11,000 isoforms and identifies structural changes across multiple metrics.

This paper introduces FoldDesign, a method for de novo protein fold design that creates novel structures from secondary structure assignments, achieving high fidelity and stability.

DeepFoldRNA couples deep self-attention neural networks with gradient-based folding simulations to predict atomic-resolution RNA tertiary structures from sequence in ~1 minute with 2.69 A average RMSD.

TripletGO improves gene function annotations by integrating transcript expression, sequence alignment, and probability models across multiple species and proteins.

The paper investigates allele-specific relationships between gene expression and genome structure in human cells using integrated haplotype-resolved data.

This study identifies potential intermediate hosts of SARS-CoV-2 by modeling Spike-RBD binding affinity to ACE2 proteins across multiple species.

ClusterMine integrates biological knowledge to cluster samples based on gene set expression profiles, improving interpretability of clusters.

The paper identifies 10 blood proteins with altered serum levels in early Lyme disease patients, developing a 10-protein panel for potential diagnostic use.

The paper updates the HPP MS Data Interpretation Guidelines to improve accuracy and address new workflows and data standards.

The paper provides considerations and recommendations for designing and analyzing plasma proteomics studies to improve translational applications in clinical settings.

The paper identifies a blood metabolome signature that robustly predicts gut microbiome α-diversity across health and disease conditions.

The paper reports a 50% reduction in PE2,3,4 missing proteins on Chromosome 17 using protein-level evidence from proteomics data.

This paper develops a probabilistic method to model functional relationships at the splice isoform level by integrating heterogeneous genomic data in mice, revealing isoform-specific interactions and functional diversity.